Wed, 23 Jul 2025

Package FastJM updated to version 1.5.1 with previous version 1.5.0 dated 2025-06-22

Title: Semi-Parametric Joint Modeling of Longitudinal and Survival Data
Description: Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and (multivariate) longitudinal data applying customized linear scan algorithms, proposed by Li and colleagues (2022) <doi:10.1155/2022/1362913>. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by shared random effects. The model is estimated using an Expectation Maximization algorithm.
Author: Shanpeng Li [aut, cre], Ning Li [ctb], Hong Wang [ctb], Jin Zhou [ctb], Hua Zhou [ctb], Gang Li [ctb]
Maintainer: Shanpeng Li <lishanpeng0913@ucla.edu>

Diff between FastJM versions 1.5.0 dated 2025-06-22 and 1.5.1 dated 2025-07-23

 DESCRIPTION        |    8 ++++----
 MD5                |   10 +++++-----
 NEWS.md            |    6 ++++++
 R/print.mvjmcs.R   |    4 ++++
 R/simmvJMdata.R    |    2 +-
 R/summary.mvjmcs.R |   23 +++++++++++++++++++++++
 6 files changed, 43 insertions(+), 10 deletions(-)

More information about FastJM at CRAN
Permanent link

Package sits updated to version 1.5.3 with previous version 1.5.2 dated 2025-02-12

Title: Satellite Image Time Series Analysis for Earth Observation Data Cubes
Description: An end-to-end toolkit for land use and land cover classification using big Earth observation data. Builds satellite image data cubes from cloud collections. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Enables merging of multi-source imagery (SAR, optical, DEM). Includes functions for quality assessment of training samples using self-organized maps and to reduce training samples imbalance. Provides machine learning algorithms including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolution neural networks, and temporal attention encoders. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference. Enables best practices for estimating area and assessing accuracy of land change. Includes object-based spatio-temporal segmentation for space-time OBIA. Minimum recomme [...truncated...]
Author: Rolf Simoes [aut], Gilberto Camara [aut, cre, ths], Felipe Souza [aut], Felipe Carlos [aut], Lorena Santos [ctb], Charlotte Pelletier [ctb], Estefania Pizarro [ctb], Karine Ferreira [ctb, ths], Alber Sanchez [ctb], Alexandre Assuncao [ctb], Daniel Fa [...truncated...]
Maintainer: Gilberto Camara <gilberto.camara.inpe@gmail.com>

Diff between sits versions 1.5.2 dated 2025-02-12 and 1.5.3 dated 2025-07-23

 sits-1.5.2/sits/R/api_preconditions.R                              |only
 sits-1.5.2/sits/R/api_raster_sub_image.R                           |only
 sits-1.5.2/sits/inst/extdata/accuracy                              |only
 sits-1.5.2/sits/inst/extdata/scripts                               |only
 sits-1.5.2/sits/inst/extdata/sources/config_source_planet.yaml     |only
 sits-1.5.2/sits/inst/extdata/tmap                                  |only
 sits-1.5.2/sits/inst/extdata/torch                                 |only
 sits-1.5.2/sits/man/sits_pred_reference.Rd                         |only
 sits-1.5.2/sits/man/sits_som.Rd                                    |only
 sits-1.5.2/sits/src/normalize_data_0.cpp                           |only
 sits-1.5.3/sits/DESCRIPTION                                        |  107 
 sits-1.5.3/sits/MD5                                                |  736 ++---
 sits-1.5.3/sits/NAMESPACE                                          |   66 
 sits-1.5.3/sits/NEWS.md                                            |   20 
 sits-1.5.3/sits/R/RcppExports.R                                    |   60 
 sits-1.5.3/sits/R/api_accessors.R                                  |    4 
 sits-1.5.3/sits/R/api_accuracy.R                                   |   76 
 sits-1.5.3/sits/R/api_apply.R                                      |  116 
 sits-1.5.3/sits/R/api_band.R                                       |   68 
 sits-1.5.3/sits/R/api_bayts.R                                      |   26 
 sits-1.5.3/sits/R/api_bbox.R                                       |   31 
 sits-1.5.3/sits/R/api_block.R                                      |   12 
 sits-1.5.3/sits/R/api_check.R                                      | 1423 ++++++----
 sits-1.5.3/sits/R/api_chunks.R                                     |  108 
 sits-1.5.3/sits/R/api_classify.R                                   |  305 +-
 sits-1.5.3/sits/R/api_clean.R                                      |   26 
 sits-1.5.3/sits/R/api_cluster.R                                    |   41 
 sits-1.5.3/sits/R/api_colors.R                                     |  126 
 sits-1.5.3/sits/R/api_combine_predictions.R                        |   44 
 sits-1.5.3/sits/R/api_comp.R                                       |   20 
 sits-1.5.3/sits/R/api_conf.R                                       |  365 +-
 sits-1.5.3/sits/R/api_crop.R                                       |   85 
 sits-1.5.3/sits/R/api_csv.R                                        |   82 
 sits-1.5.3/sits/R/api_cube.R                                       |  657 ++--
 sits-1.5.3/sits/R/api_data.R                                       | 1069 ++-----
 sits-1.5.3/sits/R/api_debug.R                                      |   10 
 sits-1.5.3/sits/R/api_detect_change.R                              |  103 
 sits-1.5.3/sits/R/api_download.R                                   |   10 
 sits-1.5.3/sits/R/api_dtw.R                                        |   36 
 sits-1.5.3/sits/R/api_environment.R                                |   15 
 sits-1.5.3/sits/R/api_factory.R                                    |    4 
 sits-1.5.3/sits/R/api_file.R                                       |   70 
 sits-1.5.3/sits/R/api_file_info.R                                  |   82 
 sits-1.5.3/sits/R/api_gdal.R                                       |  118 
 sits-1.5.3/sits/R/api_gdalcubes.R                                  |  164 -
 sits-1.5.3/sits/R/api_grid.R                                       |  119 
 sits-1.5.3/sits/R/api_jobs.R                                       |   27 
 sits-1.5.3/sits/R/api_kohonen.R                                    |  259 -
 sits-1.5.3/sits/R/api_label_class.R                                |   54 
 sits-1.5.3/sits/R/api_mask.R                                       |    8 
 sits-1.5.3/sits/R/api_merge.R                                      |  293 +-
 sits-1.5.3/sits/R/api_message.R                                    |only
 sits-1.5.3/sits/R/api_mixture_model.R                              |   27 
 sits-1.5.3/sits/R/api_ml_model.R                                   |   64 
 sits-1.5.3/sits/R/api_mosaic.R                                     |   78 
 sits-1.5.3/sits/R/api_opensearch.R                                 |   80 
 sits-1.5.3/sits/R/api_parallel.R                                   |   60 
 sits-1.5.3/sits/R/api_patterns.R                                   |    5 
 sits-1.5.3/sits/R/api_period.R                                     |    5 
 sits-1.5.3/sits/R/api_plot_raster.R                                |  172 -
 sits-1.5.3/sits/R/api_plot_time_series.R                           |  101 
 sits-1.5.3/sits/R/api_plot_vector.R                                |   41 
 sits-1.5.3/sits/R/api_point.R                                      |    4 
 sits-1.5.3/sits/R/api_predictors.R                                 |   69 
 sits-1.5.3/sits/R/api_raster.R                                     |  769 +++--
 sits-1.5.3/sits/R/api_reclassify.R                                 |   31 
 sits-1.5.3/sits/R/api_reduce.R                                     |   38 
 sits-1.5.3/sits/R/api_regularize.R                                 |  246 +
 sits-1.5.3/sits/R/api_request.R                                    |    6 
 sits-1.5.3/sits/R/api_request_httr2.R                              |   26 
 sits-1.5.3/sits/R/api_roi.R                                        |   39 
 sits-1.5.3/sits/R/api_samples.R                                    |  246 +
 sits-1.5.3/sits/R/api_segments.R                                   |   56 
 sits-1.5.3/sits/R/api_select.R                                     |   70 
 sits-1.5.3/sits/R/api_sf.R                                         |  130 
 sits-1.5.3/sits/R/api_shp.R                                        |   28 
 sits-1.5.3/sits/R/api_signal.R                                     |   22 
 sits-1.5.3/sits/R/api_smooth.R                                     |   37 
 sits-1.5.3/sits/R/api_smote.R                                      |   27 
 sits-1.5.3/sits/R/api_som.R                                        |  103 
 sits-1.5.3/sits/R/api_source.R                                     |  231 -
 sits-1.5.3/sits/R/api_source_aws.R                                 |   23 
 sits-1.5.3/sits/R/api_source_bdc.R                                 |   13 
 sits-1.5.3/sits/R/api_source_cdse.R                                |  378 --
 sits-1.5.3/sits/R/api_source_cdse_os.R                             |only
 sits-1.5.3/sits/R/api_source_deafrica.R                            |   95 
 sits-1.5.3/sits/R/api_source_deaustralia.R                         |   39 
 sits-1.5.3/sits/R/api_source_hls.R                                 |   62 
 sits-1.5.3/sits/R/api_source_local.R                               |  384 +-
 sits-1.5.3/sits/R/api_source_mpc.R                                 |  389 ++
 sits-1.5.3/sits/R/api_source_ogh.R                                 |only
 sits-1.5.3/sits/R/api_source_sdc.R                                 |   38 
 sits-1.5.3/sits/R/api_source_stac.R                                |   82 
 sits-1.5.3/sits/R/api_source_terrascope.R                          |  147 -
 sits-1.5.3/sits/R/api_source_usgs.R                                |   28 
 sits-1.5.3/sits/R/api_space_time_operations.R                      |   83 
 sits-1.5.3/sits/R/api_stac.R                                       |  168 -
 sits-1.5.3/sits/R/api_stats.R                                      |   19 
 sits-1.5.3/sits/R/api_summary.R                                    |    3 
 sits-1.5.3/sits/R/api_texture.R                                    |only
 sits-1.5.3/sits/R/api_tibble.R                                     |  108 
 sits-1.5.3/sits/R/api_tile.R                                       |  469 +--
 sits-1.5.3/sits/R/api_timeline.R                                   |   99 
 sits-1.5.3/sits/R/api_tmap.R                                       |  187 -
 sits-1.5.3/sits/R/api_torch.R                                      |   66 
 sits-1.5.3/sits/R/api_torch_psetae.R                               |  145 -
 sits-1.5.3/sits/R/api_ts.R                                         |   77 
 sits-1.5.3/sits/R/api_tuning.R                                     |   52 
 sits-1.5.3/sits/R/api_uncertainty.R                                |   71 
 sits-1.5.3/sits/R/api_utils.R                                      |   29 
 sits-1.5.3/sits/R/api_validate.R                                   |    5 
 sits-1.5.3/sits/R/api_values.R                                     |   10 
 sits-1.5.3/sits/R/api_variance.R                                   |   32 
 sits-1.5.3/sits/R/api_vector_info.R                                |    5 
 sits-1.5.3/sits/R/api_view.R                                       |  369 +-
 sits-1.5.3/sits/R/sits-package.R                                   |   25 
 sits-1.5.3/sits/R/sits_accuracy.R                                  |  200 -
 sits-1.5.3/sits/R/sits_add_base_cube.R                             |   79 
 sits-1.5.3/sits/R/sits_apply.R                                     |  125 
 sits-1.5.3/sits/R/sits_bands.R                                     |   31 
 sits-1.5.3/sits/R/sits_bayts.R                                     |   17 
 sits-1.5.3/sits/R/sits_bbox.R                                      |   36 
 sits-1.5.3/sits/R/sits_classify.R                                  |  601 ++--
 sits-1.5.3/sits/R/sits_clean.R                                     |  142 
 sits-1.5.3/sits/R/sits_cluster.R                                   |   42 
 sits-1.5.3/sits/R/sits_colors.R                                    |   72 
 sits-1.5.3/sits/R/sits_combine_predictions.R                       |   62 
 sits-1.5.3/sits/R/sits_config.R                                    |   38 
 sits-1.5.3/sits/R/sits_csv.R                                       |   45 
 sits-1.5.3/sits/R/sits_cube.R                                      |  752 ++---
 sits-1.5.3/sits/R/sits_cube_copy.R                                 |  109 
 sits-1.5.3/sits/R/sits_cube_local.R                                |only
 sits-1.5.3/sits/R/sits_detect_change.R                             |   31 
 sits-1.5.3/sits/R/sits_detect_change_method.R                      |   10 
 sits-1.5.3/sits/R/sits_dtw.R                                       |   37 
 sits-1.5.3/sits/R/sits_factory.R                                   |    7 
 sits-1.5.3/sits/R/sits_filters.R                                   |   29 
 sits-1.5.3/sits/R/sits_geo_dist.R                                  |   27 
 sits-1.5.3/sits/R/sits_get_class.R                                 |   87 
 sits-1.5.3/sits/R/sits_get_data.R                                  |  547 +++
 sits-1.5.3/sits/R/sits_get_probs.R                                 |  104 
 sits-1.5.3/sits/R/sits_grid_systems.R                              |only
 sits-1.5.3/sits/R/sits_histogram.R                                 |   53 
 sits-1.5.3/sits/R/sits_imputation.R                                |   15 
 sits-1.5.3/sits/R/sits_label_classification.R                      |   78 
 sits-1.5.3/sits/R/sits_labels.R                                    |   43 
 sits-1.5.3/sits/R/sits_lighttae.R                                  |   82 
 sits-1.5.3/sits/R/sits_machine_learning.R                          |  262 +
 sits-1.5.3/sits/R/sits_merge.R                                     |   46 
 sits-1.5.3/sits/R/sits_mixture_model.R                             |   73 
 sits-1.5.3/sits/R/sits_mlp.R                                       |   76 
 sits-1.5.3/sits/R/sits_model_export.R                              |    7 
 sits-1.5.3/sits/R/sits_mosaic.R                                    |   30 
 sits-1.5.3/sits/R/sits_patterns.R                                  |   22 
 sits-1.5.3/sits/R/sits_plot.R                                      |  746 ++---
 sits-1.5.3/sits/R/sits_predictors.R                                |   72 
 sits-1.5.3/sits/R/sits_reclassify.R                                |  186 -
 sits-1.5.3/sits/R/sits_reduce.R                                    |   39 
 sits-1.5.3/sits/R/sits_reduce_imbalance.R                          |   68 
 sits-1.5.3/sits/R/sits_regularize.R                                |  326 +-
 sits-1.5.3/sits/R/sits_resnet.R                                    |only
 sits-1.5.3/sits/R/sits_sample_functions.R                          |  383 --
 sits-1.5.3/sits/R/sits_segmentation.R                              |  149 -
 sits-1.5.3/sits/R/sits_select.R                                    |   77 
 sits-1.5.3/sits/R/sits_sf.R                                        |   34 
 sits-1.5.3/sits/R/sits_smooth.R                                    |   88 
 sits-1.5.3/sits/R/sits_som.R                                       |  202 -
 sits-1.5.3/sits/R/sits_stars.R                                     |only
 sits-1.5.3/sits/R/sits_summary.R                                   |  208 -
 sits-1.5.3/sits/R/sits_tae.R                                       |   64 
 sits-1.5.3/sits/R/sits_tempcnn.R                                   |  123 
 sits-1.5.3/sits/R/sits_terra.R                                     |only
 sits-1.5.3/sits/R/sits_texture.R                                   |only
 sits-1.5.3/sits/R/sits_timeline.R                                  |   34 
 sits-1.5.3/sits/R/sits_train.R                                     |   40 
 sits-1.5.3/sits/R/sits_tuning.R                                    |   64 
 sits-1.5.3/sits/R/sits_uncertainty.R                               |  266 +
 sits-1.5.3/sits/R/sits_utils.R                                     |    8 
 sits-1.5.3/sits/R/sits_validate.R                                  |   62 
 sits-1.5.3/sits/R/sits_variance.R                                  |   97 
 sits-1.5.3/sits/R/sits_view.R                                      |  186 -
 sits-1.5.3/sits/R/sits_xlsx.R                                      |   26 
 sits-1.5.3/sits/R/zzz.R                                            |   16 
 sits-1.5.3/sits/demo/classify_cbers_bdc.R                          |    2 
 sits-1.5.3/sits/demo/classify_deeplearning.R                       |    2 
 sits-1.5.3/sits/demo/dl_comparison.R                               |    9 
 sits-1.5.3/sits/demo/ml_comparison.R                               |    6 
 sits-1.5.3/sits/inst/WORDLIST                                      |   75 
 sits-1.5.3/sits/inst/extdata/config_colors.yml                     |  180 +
 sits-1.5.3/sits/inst/extdata/config_internals.yml                  |   10 
 sits-1.5.3/sits/inst/extdata/config_messages.yml                   |  111 
 sits-1.5.3/sits/inst/extdata/config_test.yml                       |only
 sits-1.5.3/sits/inst/extdata/cran/check_package_cran.R             |    3 
 sits-1.5.3/sits/inst/extdata/cran/pkg_size_functions.R             |    3 
 sits-1.5.3/sits/inst/extdata/cran/sits_codecov.R                   |   17 
 sits-1.5.3/sits/inst/extdata/sources/config_source_aws.yml         |    6 
 sits-1.5.3/sits/inst/extdata/sources/config_source_bdc.yml         |    8 
 sits-1.5.3/sits/inst/extdata/sources/config_source_cdse.yml        |  103 
 sits-1.5.3/sits/inst/extdata/sources/config_source_cdse_os.yml     |only
 sits-1.5.3/sits/inst/extdata/sources/config_source_chile.yml       |    2 
 sits-1.5.3/sits/inst/extdata/sources/config_source_deafrica.yml    |   10 
 sits-1.5.3/sits/inst/extdata/sources/config_source_deaustralia.yml |   12 
 sits-1.5.3/sits/inst/extdata/sources/config_source_hls.yml         |    4 
 sits-1.5.3/sits/inst/extdata/sources/config_source_mpc.yml         |  153 -
 sits-1.5.3/sits/inst/extdata/sources/config_source_ogh.yml         |only
 sits-1.5.3/sits/inst/extdata/sources/config_source_planet.yml      |only
 sits-1.5.3/sits/inst/extdata/sources/config_source_sdc.yml         |    2 
 sits-1.5.3/sits/inst/extdata/sources/config_source_terrascope.yml  |   22 
 sits-1.5.3/sits/inst/extdata/sources/config_source_usgs.yml        |    4 
 sits-1.5.3/sits/man/dot-check_date_parameter.Rd                    |    4 
 sits-1.5.3/sits/man/hist.probs_cube.Rd                             |    2 
 sits-1.5.3/sits/man/hist.raster_cube.Rd                            |    9 
 sits-1.5.3/sits/man/hist.sits.Rd                                   |    9 
 sits-1.5.3/sits/man/hist.uncertainty_cube.Rd                       |    2 
 sits-1.5.3/sits/man/plot.Rd                                        |    9 
 sits-1.5.3/sits/man/plot.class_cube.Rd                             |    6 
 sits-1.5.3/sits/man/plot.class_vector_cube.Rd                      |    2 
 sits-1.5.3/sits/man/plot.dem_cube.Rd                               |   12 
 sits-1.5.3/sits/man/plot.geo_distances.Rd                          |    2 
 sits-1.5.3/sits/man/plot.patterns.Rd                               |    5 
 sits-1.5.3/sits/man/plot.predicted.Rd                              |    3 
 sits-1.5.3/sits/man/plot.probs_cube.Rd                             |    4 
 sits-1.5.3/sits/man/plot.probs_vector_cube.Rd                      |   26 
 sits-1.5.3/sits/man/plot.raster_cube.Rd                            |   50 
 sits-1.5.3/sits/man/plot.sar_cube.Rd                               |   11 
 sits-1.5.3/sits/man/plot.sits_accuracy.Rd                          |    2 
 sits-1.5.3/sits/man/plot.sits_cluster.Rd                           |    7 
 sits-1.5.3/sits/man/plot.som_clean_samples.Rd                      |    2 
 sits-1.5.3/sits/man/plot.som_map.Rd                                |    6 
 sits-1.5.3/sits/man/plot.torch_model.Rd                            |    4 
 sits-1.5.3/sits/man/plot.uncertainty_cube.Rd                       |    6 
 sits-1.5.3/sits/man/plot.uncertainty_vector_cube.Rd                |   18 
 sits-1.5.3/sits/man/plot.variance_cube.Rd                          |    7 
 sits-1.5.3/sits/man/plot.vector_cube.Rd                            |   12 
 sits-1.5.3/sits/man/plot.xgb_model.Rd                              |    2 
 sits-1.5.3/sits/man/print.sits_area_accuracy.Rd                    |    2 
 sits-1.5.3/sits/man/sits-package.Rd                                |   39 
 sits-1.5.3/sits/man/sits_accuracy.Rd                               |   43 
 sits-1.5.3/sits/man/sits_add_base_cube.Rd                          |   74 
 sits-1.5.3/sits/man/sits_apply.Rd                                  |   71 
 sits-1.5.3/sits/man/sits_as_sf.Rd                                  |    8 
 sits-1.5.3/sits/man/sits_as_stars.Rd                               |only
 sits-1.5.3/sits/man/sits_as_terra.Rd                               |only
 sits-1.5.3/sits/man/sits_bands.Rd                                  |    2 
 sits-1.5.3/sits/man/sits_bbox.Rd                                   |   23 
 sits-1.5.3/sits/man/sits_classify.Rd                               |  297 --
 sits-1.5.3/sits/man/sits_classify.raster_cube.Rd                   |only
 sits-1.5.3/sits/man/sits_classify.segs_cube.Rd                     |only
 sits-1.5.3/sits/man/sits_classify.sits.Rd                          |only
 sits-1.5.3/sits/man/sits_clean.Rd                                  |  105 
 sits-1.5.3/sits/man/sits_cluster_clean.Rd                          |    2 
 sits-1.5.3/sits/man/sits_cluster_dendro.Rd                         |    5 
 sits-1.5.3/sits/man/sits_cluster_frequency.Rd                      |    2 
 sits-1.5.3/sits/man/sits_colors.Rd                                 |   10 
 sits-1.5.3/sits/man/sits_colors_qgis.Rd                            |   35 
 sits-1.5.3/sits/man/sits_combine_predictions.Rd                    |   30 
 sits-1.5.3/sits/man/sits_confidence_sampling.Rd                    |   23 
 sits-1.5.3/sits/man/sits_config.Rd                                 |    5 
 sits-1.5.3/sits/man/sits_config_user_file.Rd                       |    2 
 sits-1.5.3/sits/man/sits_cube.Rd                                   |  484 ---
 sits-1.5.3/sits/man/sits_cube.local_cube.Rd                        |only
 sits-1.5.3/sits/man/sits_cube.results_cube.Rd                      |only
 sits-1.5.3/sits/man/sits_cube.stac_cube.Rd                         |only
 sits-1.5.3/sits/man/sits_cube.vector_cube.Rd                       |only
 sits-1.5.3/sits/man/sits_cube_copy.Rd                              |   53 
 sits-1.5.3/sits/man/sits_factory_function.Rd                       |    2 
 sits-1.5.3/sits/man/sits_filter.Rd                                 |    3 
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Package predictsr updated to version 0.1.1 with previous version 0.1.0 dated 2025-07-10

Title: Access the 'PREDICTS' Biodiversity Database
Description: Fetches the 'PREDICTS' database and relevant metadata from the Data Portal at the Natural History Museum, London <https://data.nhm.ac.uk>. Data were collated from over 400 existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from sites around the world. These data are described in Hudson et al. (2013) <doi:10.1002/ece3.2579>.
Author: Connor Duffin [aut, cre], The Trustees of The Natural History Museum, London [cph]
Maintainer: Connor Duffin <connor.p.duffin@gmail.com>

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Package PPforest updated to version 0.2.0 with previous version 0.1.3 dated 2022-09-09

Title: Projection Pursuit Classification Forest
Description: Implements projection pursuit forest algorithm for supervised classification.
Author: Natalia da Silva [aut, cre] , Dianne Cook [aut], Eun-Kyung Lee [aut]
Maintainer: Natalia da Silva <natalia.dasilva@fcea.edu.uy>

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Package mbX updated to version 0.2.0 with previous version 0.1.3 dated 2025-03-03

Title: A Comprehensive Microbiome Data Processing Pipeline
Description: Provides tools for cleaning, processing, and preparing microbiome sequencing data (e.g., 16S rRNA) for downstream analysis. Supports CSV, TXT, and Excel file formats. The main function, ezclean(), automates microbiome data transformation, including format validation, transposition, numeric conversion, and metadata integration. It also handles taxonomic levels efficiently, resolves duplicated taxa entries, and outputs a well-structured, analysis-ready dataset. The companion functions ezstat() run statistical tests and summarize results, while ezviz() produces publication-ready visualizations.
Author: Utsav Lamichhane [aut, cre]
Maintainer: Utsav Lamichhane <utsav.lamichhane@gmail.com>

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Package dynaSpec updated to version 1.0.4 with previous version 1.0.3 dated 2025-04-07

Title: Dynamic Spectrogram Visualizations
Description: A set of tools to generate dynamic spectrogram visualizations in video format.
Author: Marcelo Araya-Salas [aut, cre]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

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Package cooltools updated to version 2.18 with previous version 2.4 dated 2024-07-18

Title: Practical Tools for Scientific Computations and Visualizations
Description: Collection of routines for efficient scientific computations in physics and astrophysics. These routines include utility functions, numerical computation tools, as well as visualisation tools. They can be used, for example, for generating random numbers from spherical and custom distributions, information and entropy analysis, special Fourier transforms, two-point correlation estimation (e.g. as in Landy & Szalay (1993) <doi:10.1086/172900>), binning & gridding of point sets, 2D interpolation, Monte Carlo integration, vector arithmetic and coordinate transformations. Also included is a non-exhaustive list of important constants and cosmological conversion functions. The graphics routines can be used to produce and export publication-ready scientific plots and movies, e.g. as used in Obreschkow et al. (2020, MNRAS Vol 493, Issue 3, Pages 4551–4569). These routines include special color scales, projection functions, and bitmap handling routines.
Author: Danail Obreschkow [aut, cre]
Maintainer: Danail Obreschkow <danail.obreschkow@gmail.com>

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Package sharp updated to version 1.4.8 with previous version 1.4.7 dated 2025-04-11

Title: Stability-enHanced Approaches using Resampling Procedures
Description: In stability selection (N Meinshausen, P Bühlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>) and consensus clustering (S Monti et al (2003) <doi:10.1023/A:1023949509487>), resampling techniques are used to enhance the reliability of the results. In this package (B Bodinier et al (2025) <doi:10.18637/jss.v112.i05>), hyper-parameters are calibrated by maximising model stability, which is measured under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2023a) <doi:10.1093/jrsssc/qlad058> and B Bodinier et al (2023b) <doi:10.1093/bioinformatics/btad635>). Functions are readily implemented for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO in stability selection, and hierarchical clustering, partitioning around medoids, K means or Gaussian mixture models in consensus clustering.
Author: Barbara Bodinier [aut, cre]
Maintainer: Barbara Bodinier <barbara.bodinier@gmail.com>

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Package FunnelPlotR updated to version 0.6.0 with previous version 0.5.0 dated 2024-04-12

Title: Funnel Plots for Comparing Institutional Performance
Description: An implementation of methods presented by Spiegelhalter (2005) <doi:10.1002/sim.1970> Funnel plots for comparing institutional performance, for standardised ratios, ratios of counts and proportions with additive overdispersion adjustment.
Author: Chris Mainey [aut, cre] , Andrew Johnson [ctb], Matthew Bass [ctb], NHS-R Community [cph]
Maintainer: Chris Mainey <c.mainey1@nhs.net>

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Package npsm updated to version 2.0.1 with previous version 2.0.0 dated 2024-05-26

Title: Nonparametric Statistical Methods
Description: Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics. Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems. Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.
Author: John Kloke [aut, cre], Joseph McKean [aut]
Maintainer: John Kloke <johndkloke@gmail.com>

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Package httk updated to version 2.7.0 with previous version 2.6.1 dated 2025-05-01

Title: High-Throughput Toxicokinetics
Description: Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predicti [...truncated...]
Author: John Wambaugh [aut, cre] , Sarah Davidson-Fritz [aut] , Robert Pearce [aut] , Caroline Ring [aut] , Greg Honda [aut] , Mark Sfeir [aut], Matt Linakis [aut] , Dustin Kapraun [aut] , Kimberly Truong [aut] , Colin Thomson [aut] , Meredith Scherer [aut] [...truncated...]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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Package grand updated to version 0.9.1 with previous version 0.9.0 dated 2023-02-10

Title: Guidelines for Reporting About Network Data
Description: Interactively applies the Guidelines for Reporting About Network Data (GRAND) to an 'igraph' object, and generates a uniform narrative or tabular description of the object.
Author: Zachary Neal [aut, cre]
Maintainer: Zachary Neal <zpneal@msu.edu>

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Package ces updated to version 1.0.0 with previous version 0.1.0 dated 2025-05-28

Title: Access to Canadian Election Study Data
Description: Provides tools to easily access and analyze Canadian Election Study data. The package simplifies the process of downloading, cleaning, and using 'CES' datasets for political science research and analysis. The Canadian Election Study ('CES') has been conducted during federal elections since 1965, surveying Canadians on their political preferences, engagement, and demographics. Data is accessed from multiple sources including the 'Borealis' Data repository <https://borealisdata.ca/> and the official 'Canadian Election Study' website <https://ces-eec.arts.ubc.ca/>. This package is not officially affiliated with the Canadian Election Study, 'Borealis' Data, or the University of British Columbia, and users should cite the original data sources in their work.
Author: Laurence-Olivier M. Foisy [aut, cre]
Maintainer: Laurence-Olivier M. Foisy <mail@mfoisy.com>

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Package bfsMaps updated to version 1.99.4 with previous version 1.99.3 dated 2023-06-30

Title: Plot Maps from Switzerland by Swiss Federal Statistical Office
Description: At the Swiss Federal Statistical Office (SFSO), spatial maps of Switzerland are available free of charge as 'Cartographic bases for small-scale thematic mapping'. This package contains convenience functions to import ESRI (Environmental Systems Research Institute) shape files using the package 'sf' and to plot them easily and quickly without having to worry too much about the technical details. It contains utilities to combine multiple areas to one single polygon and to find neighbours for single regions. For any point on a map, a special locator can be used to determine to which municipality, district or canton it belongs.
Author: Andri Signorell [aut, cre], Juerg Guggenbuehl [ctb]
Maintainer: Andri Signorell <andri@signorell.net>

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New package triplediff with initial version 0.1.0
Package: triplediff
Title: Triple-Difference Estimators
Version: 0.1.0
Description: Implements triple-difference (DDD) estimators for both average treatment effects and event-study parameters. Methods include regression adjustment, inverse-probability weighting, and doubly-robust estimators, all of which rely on a conditional DDD parallel-trends assumption and allow covariate adjustment across multiple pre- and post-treatment periods. The methodology is detailed in Ortiz-Villavicencio and Sant'Anna (2025) <doi:10.48550/arXiv.2505.09942>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3)
Imports: BMisc (>= 1.4.6), data.table (>= 1.15.0), Matrix (>= 1.6.1), parallel (>= 1.4.0), parglm (>= 0.1.7), Rcpp (>= 1.0.12), speedglm (>= 0.3-5)
LinkingTo: Rcpp (>= 1.0.12)
Suggests: testthat (>= 3.0.0)
URL: http://marcelortiz.com/triplediff/
NeedsCompilation: yes
Packaged: 2025-07-22 16:51:53 UTC; marcelortizv
Author: Marcelo Ortiz-Villavicencio [aut, cre], Pedro H. C. Sant'Anna [aut]
Maintainer: Marcelo Ortiz-Villavicencio <marcelo.ortiz@emory.edu>
Repository: CRAN
Date/Publication: 2025-07-23 19:10:02 UTC

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Package statquotes updated to version 0.3.3 with previous version 0.3.2 dated 2023-10-10

Title: Quotes on Statistics, Data Visualization and Science
Description: Generates a random quotation from a database of quotes on topics in statistics, data visualization and science. Other functions allow searching the quotes database by key term tags, or authors or creating a word cloud. The output is designed to be suitable for use at the console, in Rmarkdown and LaTeX.
Author: Michael Friendly [aut, cre] , Kevin Wright [aut] , Phil Chalmers [aut], Matthew Sigal [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

Diff between statquotes versions 0.3.2 dated 2023-10-10 and 0.3.3 dated 2025-07-23

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New package shoppingwords with initial version 0.1.0
Package: shoppingwords
Title: Text Processing Tools for Turkish E-Commerce Data
Description: Provides several datasets useful for processing and analysis of text in Turkish from an online shopping platform.
Version: 0.1.0
Maintainer: Betul Kan-Kilinc <bkan@eskisehir.edu.tr>
Imports: stringi, stopwords, stringdist, tibble
Depends: R (>= 4.0.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, dplyr, ggplot2
VignetteBuilder: knitr
LazyDataCompression: xz
URL: https://bkanx.github.io/shoppingwords/
NeedsCompilation: no
Packaged: 2025-07-22 19:48:22 UTC; mac
Author: Betul Kan-Kilinc [aut, cre] , Mine Cetinkaya-Rundel [ctb] , Colin Rundel [ctb]
Repository: CRAN
Date/Publication: 2025-07-23 19:20:02 UTC

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Package RGraphSpace updated to version 1.0.9 with previous version 1.0.8 dated 2025-05-14

Title: A Lightweight Interface Between 'ggplot2' and 'igraph' Objects
Description: Interface to integrate 'igraph' and 'ggplot2' graphics within spatial maps. 'RGraphSpace' implements new geometric objects using 'ggplot2' prototypes, customized for representing large 'igraph' objects in a normalized coordinate system. By scaling shapes and graph elements, 'RGraphSpace' can provide a framework for layered visualizations.
Author: Victor Apolonio [ctb], Vinicius Chagas [ctb], Mauro Castro [aut, cre]
Maintainer: Mauro Castro <mauro.a.castro@gmail.com>

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New package HIViz with initial version 0.1.2
Package: HIViz
Title: Interactive Dashboard for 'HIV' Data Visualization
Version: 0.1.2
Description: An interactive 'Shiny' dashboard for visualizing and exploring key metrics related to HIV/AIDS, including prevalence, incidence, mortality, and treatment coverage. The dashboard is designed to work with a dataset containing specific columns with standardized names. These columns must be present in the input data for the app to function properly: year: Numeric year of the data (e.g. 2010, 2021); sex: Gender classification (e.g. Male, Female); age_group: Age bracket (e.g. 15–24, 25–34); hiv_prevalence: Estimated HIV prevalence percentage; hiv_incidence: Number of new HIV cases per year; aids_deaths: Total AIDS-related deaths; plhiv: Estimated number of people living with HIV; art_coverage: Percentage receiving antiretroviral therapy (ART); testing_coverage: HIV testing services coverage; causes: Description of likely HIV transmission cause (e.g. unprotected sex, drug use). The dataset structure must strictly follow this column naming convention for the dashboard to render correctly.
Depends: R(>= 3.5.0)
VignetteBuilder: knitr
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: shiny (>= 1.7.0), shinydashboard, readxl, haven, dplyr, DT, ggplot2, plotly, tidyr,wordcloud, ggrepel, paletteer, shinyWidgets, tools
URL: https://github.com/Atefehrashidi/HIViz
BugReports: https://github.com/Atefehrashidi/HIViz/issues
NeedsCompilation: no
Packaged: 2025-07-22 20:23:45 UTC; Administrator
Author: Atefeh Rashidi Pour [aut, cre] , Marzieh Rashidipour [aut]
Maintainer: Atefeh Rashidi Pour <rashidiatefeh98@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-23 19:20:08 UTC

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New package enaho with initial version 0.2.0
Package: enaho
Title: Encuesta Nacional de Hogares (Peruvian Home National Survey)
Version: 0.2.0
Maintainer: Andres Christiansen <andres.christiansen@iea-hamburg.de>
Description: Descarga, lee y combina bases de la Encuesta Nacional de Hogares (ENAHO) del Instituto Nacional de Estadística e Informática (INEI) del Perú. (Downloads, reads, and combines data from the Peruvian Home National Survey.)
License: GPL (>= 2.0)
Encoding: UTF-8
Language: es
Depends: R (>= 3.5)
Imports: haven, tibble
URL: https://dopatendo.github.io/enaho/
NeedsCompilation: no
Packaged: 2025-07-22 16:39:23 UTC; andreschristiansen
Author: Andres Christiansen [aut, cre]
Repository: CRAN
Date/Publication: 2025-07-23 19:10:08 UTC

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Package dfmirroR updated to version 2.2.0 with previous version 2.1.0 dated 2024-01-26

Title: Simulate a Data Frame Mirroring an Input and Produce Shareable Simulation Code
Description: The 'dfmirroR' package allows users to input a data frame, simulate some number of observations based on specified columns of that data frame, and then outputs a string that contains the code to re-create the simulation. The goal is to both provide workable test data sets and provide users with the information they need to set up reproducible examples with team members. This package was created out of a need to share examples in cases where data are private and where a full data frame is not needed for testing or coordinating.
Author: Jacob Patterson-Stein [aut, cre]
Maintainer: Jacob Patterson-Stein <jacobpstein@gmail.com>

Diff between dfmirroR versions 2.1.0 dated 2024-01-26 and 2.2.0 dated 2025-07-23

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Package ctqr updated to version 2.2 with previous version 2.1 dated 2024-02-12

Title: Censored and Truncated Quantile Regression
Description: Estimation of quantile regression models for survival data.
Author: Paolo Frumento [aut, cre]
Maintainer: Paolo Frumento <paolo.frumento@unipi.it>

Diff between ctqr versions 2.1 dated 2024-02-12 and 2.2 dated 2025-07-23

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Package clickstream updated to version 1.3.4 with previous version 1.3.3 dated 2023-09-27

Title: Analyzes Clickstreams Based on Markov Chains
Description: A set of tools to read, analyze and write lists of click sequences on websites (i.e., clickstream). A click can be represented by a number, character or string. Clickstreams can be modeled as zero- (only computes occurrence probabilities), first- or higher-order Markov chains.
Author: Michael Scholz [aut, cre], Theo van Kraay [aut]
Maintainer: Michael Scholz <michael.scholz@th-deg.de>

Diff between clickstream versions 1.3.3 dated 2023-09-27 and 1.3.4 dated 2025-07-23

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Package vimp updated to version 2.3.5 with previous version 2.3.3 dated 2023-08-28

Title: Perform Inference on Algorithm-Agnostic Variable Importance
Description: Calculate point estimates of and valid confidence intervals for nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (Biometrics, 2020), Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020).
Author: Brian D. Williamson [aut, cre] , Jean Feng [ctb], Charlie Wolock [ctb], Noah Simon [ths] , Marco Carone [ths]
Maintainer: Brian D. Williamson <brian.d.williamson@kp.org>

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Package spBayesSurv updated to version 1.1.9 with previous version 1.1.8 dated 2024-02-23

Title: Bayesian Modeling and Analysis of Spatially Correlated Survival Data
Description: Provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed Polya tree density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou, Hanson and Zhang (2020) <doi:10.18637/jss.v092.i09>.
Author: Haiming Zhou [aut, cre, cph], Timothy Hanson [aut]
Maintainer: Haiming Zhou <haiming2019@gmail.com>

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Package rddapp updated to version 1.3.3 with previous version 1.3.2 dated 2023-04-05

Title: Regression Discontinuity Design Application
Description: Estimation of both single- and multiple-assignment Regression Discontinuity Designs (RDDs). Provides both parametric (global) and non-parametric (local) estimation choices for both sharp and fuzzy designs, along with power analysis and assumption checks. Introductions to the underlying logic and analysis of RDDs are in Thistlethwaite, D. L., Campbell, D. T. (1960) <doi:10.1037/h0044319> and Lee, D. S., Lemieux, T. (2010) <doi:10.1257/jel.48.2.281>.
Author: Ze Jin [aut], Wang Liao [aut], Irena Papst [aut], Wenyu Zhang [aut], Kimberly Hochstedler [aut], Felix Thoemmes [aut, cre]
Maintainer: Felix Thoemmes <fjt36@cornell.edu>

Diff between rddapp versions 1.3.2 dated 2023-04-05 and 1.3.3 dated 2025-07-23

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Package RcmdrMisc updated to version 2.9-2 with previous version 2.9-1 dated 2023-09-26

Title: R Commander Miscellaneous Functions
Description: Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.
Author: John Fox [aut, cre], Manuel Marquez [aut], Robert Muenchen [ctb], Dan Putler [ctb]
Maintainer: John Fox <jfox@mcmaster.ca>

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New package quitefastmst with initial version 0.9.0
Package: quitefastmst
Title: Euclidean and Mutual Reachability Minimum Spanning Trees
Version: 0.9.0
Date: 2025-07-22
Description: Functions to compute Euclidean minimum spanning trees using single-, sesqui-, and dual-tree Boruvka algorithms. Thanks to K-d trees, they are fast in spaces of low intrinsic dimensionality. Mutual reachability distances (used in the definition of the 'HDBSCAN*' algorithm) are also supported. The package also features relatively fast fallback minimum spanning tree and nearest-neighbours algorithms for spaces of higher dimensionality. The 'Python' version of 'quitefastmst' is available via 'PyPI'.
BugReports: https://github.com/gagolews/quitefastmst/issues
URL: https://quitefastmst.gagolewski.com/, https://github.com/gagolews/quitefastmst
License: AGPL-3
Imports: Rcpp
Suggests: datasets
LinkingTo: Rcpp
Encoding: UTF-8
SystemRequirements: OpenMP, C++17
NeedsCompilation: yes
Packaged: 2025-07-22 13:01:08 UTC; gagolews
Author: Marek Gagolewski [aut, cre, cph]
Maintainer: Marek Gagolewski <marek@gagolewski.com>
Repository: CRAN
Date/Publication: 2025-07-23 19:00:11 UTC

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Package QHScrnomo updated to version 3.0.2 with previous version 3.0.1 dated 2024-03-18

Title: Construct Nomograms for Competing Risks Regression Models
Description: Nomograms are constructed to predict the cumulative incidence rate which is calculated after adjusting for competing causes to the event of interest. K-fold cross-validation is implemented to validate predictive accuracy using a competing-risk version of the concordance index. Methods are as described in: Kattan MW, Heller G, Brennan MF (2003).
Author: Michael Kattan [aut], Changhong Yu [aut], Xinge Ji [aut], Zajichek Alex [cre]
Maintainer: Zajichek Alex <zajicha2@ccf.org>

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Package pch updated to version 2.2 with previous version 2.1 dated 2024-02-09

Title: Piecewise Constant Hazard Models for Censored and Truncated Data
Description: Piecewise constant hazard models for survival data. The package allows for right-censored, left-truncated, and interval-censored data.
Author: Paolo Frumento [aut, cre]
Maintainer: Paolo Frumento <paolo.frumento@unipi.it>

Diff between pch versions 2.1 dated 2024-02-09 and 2.2 dated 2025-07-23

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Package mvinfluence updated to version 0.9.2 with previous version 0.9.0 dated 2022-09-20

Title: Influence Measures and Diagnostic Plots for Multivariate Linear Models
Description: Computes regression deletion diagnostics for multivariate linear models and provides some associated diagnostic plots. The diagnostic measures include hat-values (leverages), generalized Cook's distance, and generalized squared 'studentized' residuals. Several types of plots to detect influential observations are provided.
Author: Michael Friendly [aut, cre]
Maintainer: Michael Friendly <friendly@yorku.ca>

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New package MDCcure with initial version 0.1.0
Package: MDCcure
Title: Martingale Dependence Tools and Testing for Mixture Cure Models
Version: 0.1.0
Description: Computes martingale difference correlation (MDC), martingale difference divergence, and their partial extensions to assess conditional mean dependence. The methods are based on Shao and Zhang (2014) <doi:10.1080/01621459.2014.887012>. Additionally, introduces a novel hypothesis test for evaluating covariate effects on the cure rate in mixture cure models, using MDC-based statistics. The methodology is described in Monroy-Castillo et al. (2025, manuscript submitted).
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, pinp
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Imports: Rcpp, RcppParallel, ggplot2, ggtext, gridExtra, future, future.apply, smcure, npcure, survival
NeedsCompilation: yes
SystemRequirements: GNU make, TBB
URL: https://github.com/CastleMon/MDCcure
BugReports: https://github.com/CastleMon/MDCcure/issues
Packaged: 2025-07-22 12:05:39 UTC; estel
Author: Blanca Monroy-Castillo [aut, cre], Amalia Jacome [aut], Ricardo Cao [aut], Ingrid Van Keilegom [aut], Ursula Mueller [aut]
Maintainer: Blanca Monroy-Castillo <blancamonroy.96@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-23 18:50:02 UTC

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New package dependentsimr with initial version 1.0.0.0
Package: dependentsimr
Title: Simulate Omics-Scale Data with Dependency
Version: 1.0.0.0
Description: Using a Gaussian copula approach, this package generates simulated data mimicking a target real dataset. It supports normal, Poisson, empirical, and 'DESeq2' (negative binomial with size factors) marginal distributions. It uses an low-rank plus diagonal covariance matrix to efficiently generate omics-scale data. Methods are described in: Yang, Grant, and Brooks (2025) <doi:10.1101/2025.01.31.634335>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: rlang (>= 1.0.0)
Suggests: DESeq2 (>= 1.40.0), S4Vectors (>= 0.44.0), SummarizedExperiment (>= 1.36.0), MASS (>= 7.3), corpcor (>= 1.6.0), testthat (>= 3.0.0), Matrix (>= 1.7), sparsesvd (>= 0.2), knitr (>= 1.50), rmarkdown, BiocManager, remotes, tidyverse (>= 2.0.0)
Depends: R (>= 4.2)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-22 15:28:25 UTC; tgb
Author: Thomas Brooks [aut, cre, cph]
Maintainer: Thomas Brooks <tgbrooks@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-23 19:00:16 UTC

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New package BKP with initial version 0.1.0
Package: BKP
Title: Beta and Dirichlet Kernel Processes for Binomial and Multinomial Modeling
Version: 0.1.0
Author: Jiangyan Zhao [cre, aut], Kunhai Qing [aut], Jin Xu [aut]
Maintainer: Jiangyan Zhao <zhaojy2017@126.com>
Description: Provides methods for nonparametric modeling of binomial and multinomial success probabilities via the Beta Kernel Process and its extension, the Dirichlet Kernel Process. Supports model fitting, predictive inference with uncertainty quantification, posterior simulation, and visualization in one- and two-dimensional input spaces. The package implements multiple kernel functions (Gaussian, Matern 5/2, and Matern 3/2), and performs hyperparameter optimization using multi-start gradient-based search. Applications include spatial statistics, probabilistic classification, and Bayesian experimental design. For more details, see MacKenzie, Trafalis, and Barker (2014) <doi:10.1002/sam.11241>.
License: GPL-3
URL: https://github.com/Jiangyan-Zhao/BKP
BugReports: https://github.com/Jiangyan-Zhao/BKP/issues
Encoding: UTF-8
NeedsCompilation: no
Depends: R (>= 3.5.0)
Imports: gridExtra, lattice, optimx, tgp
Suggests: stats, testthat (>= 3.0.0)
Packaged: 2025-07-22 13:10:58 UTC; JYZHAO
Repository: CRAN
Date/Publication: 2025-07-23 18:50:07 UTC

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Package TapeS updated to version 0.13.4 with previous version 0.13.3 dated 2025-02-14

Title: Tree Taper Curves and Sorting Based on 'TapeR'
Description: Providing new german-wide 'TapeR' Models and functions for their evaluation. Included are the most common tree species in Germany (Norway spruce, Scots pine, European larch, Douglas fir, Silver fir as well as European beech, Common/Sessile oak and Red oak). Many other species are mapped to them so that 36 tree species / groups can be processed. Single trees are defined by species code, one or multiple diameters in arbitrary measuring height and tree height. The functions then provide information on diameters along the stem, bark thickness, height of diameters, volume of the total or parts of the trunk and total and component above-ground biomass. It is also possible to calculate assortments from the taper curves. Uncertainty information is provided for diameter, volume and component biomass estimation.
Author: Christian Vonderach [aut, cre], Edgar Kublin [aut], Gerald Kaendler [aut]
Maintainer: Christian Vonderach <christian.vonderach@forst.bwl.de>

Diff between TapeS versions 0.13.3 dated 2025-02-14 and 0.13.4 dated 2025-07-23

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Package reproducibleRchunks updated to version 1.2.0 with previous version 1.1.0 dated 2025-07-02

Title: Automated Reproducibility Checks for R Markdown Documents
Description: Provide reproducible R chunks in R Markdown document that automatically check computational results for reproducibility. This is achieved by creating json files storing metadata about computational results. A comprehensive tutorial to the package is available as preprint by Brandmaier & Peikert (2024, <doi:10.31234/osf.io/3zjvf>).
Author: Andreas M. Brandmaier [aut, cre], Aaron Peikert [ctb]
Maintainer: Andreas M. Brandmaier <andreas.brandmaier@medicalschool-berlin.de>

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Package qlcal updated to version 0.0.16 with previous version 0.0.15 dated 2025-04-23

Title: R Bindings to the Calendaring Functionality of 'QuantLib'
Description: 'QuantLib' bindings are provided for R using 'Rcpp' via an evolved version of the initial header-only 'Quantuccia' project offering an subset of 'QuantLib' (now maintained separately just for the calendaring subset). See the included file 'AUTHORS' for a full list of contributors to 'QuantLib' (and hence also 'Quantuccia').
Author: Dirk Eddelbuettel [aut, cre] , QuantLib Authors [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package ProfileLadder updated to version 0.1.3 with previous version 0.1.2 dated 2025-06-11

Title: Functional Profile Chain Ladder for Claims Reserving
Description: Functional claims reserving methods based on aggregated chain-ladder data, also known as the run-off triangle (functional) development profiles, implemented in three nonparametric algorithms (PARALLAX, REACT, and MACRAME) proposed in Maciak, Mizera, and Pešta (2022) <doi:10.1017/asb.2022.4>.
Author: Matus Maciak [aut, cre], Rastislav Matus [ctb], Ivan Mizera [aut], Michal Pesta [aut]
Maintainer: Matus Maciak <maciak@karlin.mff.cuni.cz>

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Package hwep updated to version 2.0.3 with previous version 2.0.2 dated 2023-05-16

Title: Hardy-Weinberg Equilibrium in Polyploids
Description: Inference concerning equilibrium and random mating in autopolyploids. Methods are available to test for equilibrium and random mating at any even ploidy level (>2) in the presence of double reduction at biallelic loci. For autopolyploid populations in equilibrium, methods are available to estimate the degree of double reduction. We also provide functions to calculate genotype frequencies at equilibrium, or after one or several rounds of random mating, given rates of double reduction. The main function is hwefit(). This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation. For details of these methods, see Gerard (2023a) <doi:10.1111/biom.13722> and Gerard (2023b) <doi:10.1111/1755-0998.13856>.
Author: David Gerard [aut, cre] , NSF DBI 2132247 [fnd]
Maintainer: David Gerard <gerard.1787@gmail.com>

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Package BrokenAdaptiveRidge updated to version 1.0.1 with previous version 1.0.0 dated 2023-04-07

Title: Broken Adaptive Ridge Regression with Cyclops
Description: Approximates best-subset selection (L0) regression with an iteratively adaptive Ridge (L2) penalty for large-scale models. This package uses Cyclops for an efficient implementation and the iterative method is described in Kawaguchi et al (2020) <doi:10.1002/sim.8438> and Li et al (2021) <doi:10.1016/j.jspi.2020.12.001>.
Author: Marc A. Suchard [aut, cre], Eric Kawaguchi [aut], Ning Li [aut], Gang Li [aut], Observational Health Data Sciences and Informatics [cph]
Maintainer: Marc A. Suchard <msuchard@ucla.edu>

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Package rUM updated to version 2.2.0 with previous version 2.1.0 dated 2025-03-21

Title: R Templates from the University of Miami
Description: This holds r markdown and quarto templates for academic papers and slide decks. It also has templates to create research projects which contain academic papers as vignettes.
Author: Raymond Balise [aut, cre] , Gabriel Odom [aut] , Kyle Grealis [aut] , Francisco Cardozo [aut] , Frank Gutierrez [ctb]
Maintainer: Raymond Balise <balise@miami.edu>

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Package Anthropometry updated to version 1.20 with previous version 1.19 dated 2023-02-22

Title: Statistical Methods for Anthropometric Data
Description: Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.
Author: Guillermo Vinue [aut, cre], Irene Epifanio [aut], Amelia Simo [aut], M. Victoria Ibanez [aut], Juan Domingo [aut], Guillermo Ayala [aut]
Maintainer: Guillermo Vinue <guillermo.vinue@uv.es>

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Package tcplfit2 updated to version 0.1.9 with previous version 0.1.8 dated 2025-04-17

Title: A Concentration-Response Modeling Utility
Description: The tcplfit2 R package performs basic concentration-response curve fitting. The original tcplFit() function in the tcpl R package performed basic concentration-response curvefitting to 3 models. With tcplfit2, the core tcpl concentration-response functionality has been expanded to process diverse high-throughput screen (HTS) data generated at the US Environmental Protection Agency, including targeted ToxCast, high-throughput transcriptomics (HTTr) and high-throughput phenotypic profiling (HTPP). tcplfit2 can be used independently to support analysis for diverse chemical screening efforts.
Author: Thomas Sheffield [aut], Jason Brown [ctb] , Sarah E. Davidson-Fritz [ctb] , Madison Feshuk [ctb, cre] , Lindsay Knupp [ctb], Zhihui Zhao [ctb], Richard S Judson [ctb] , Katie Paul Friedman [ctb]
Maintainer: Madison Feshuk <feshuk.madison@epa.gov>

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Package neurobase updated to version 1.33.0 with previous version 1.32.4 dated 2024-05-09

Title: 'Neuroconductor' Base Package with Helper Functions for 'nifti' Objects
Description: Base package for 'Neuroconductor', which includes many helper functions that interact with objects of class 'nifti', implemented by package 'oro.nifti', for reading/writing and also other manipulation functions.
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package missMDA updated to version 1.20 with previous version 1.19 dated 2023-11-17

Title: Handling Missing Values with Multivariate Data Analysis
Description: Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.
Author: Francois Husson [aut, cre] , Julie Josse [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package meta updated to version 8.2-0 with previous version 8.1-0 dated 2025-05-02

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - common effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - three-level meta-analysis model; - generalised linear mixed model; - logistic regression with penalised likelihood for rare events; - Hartung-Knapp method for random effects model; - Kenward-Roger method for random effects model; - prediction interval; - statistical tests for funnel plot asymmetry; - trim-and-fill method to evaluate bias in meta-analysis; - meta-regression; - cumulative meta-analysis and leave-one-out meta-analysis; - import data from 'RevMan 5'; - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package biostat3 updated to version 0.2.3 with previous version 0.2.2 dated 2024-10-29

Title: Utility Functions, Datasets and Extended Examples for Survival Analysis
Description: Utility functions, datasets and extended examples for survival analysis. This extends a range of other packages, some simple wrappers for time-to-event analyses, datasets, and extensive examples in HTML with R scripts. The package also supports the course Biostatistics III entitled "Survival analysis for epidemiologists in R".
Author: Annika Tillander [ctb], Andreas Karlsson [aut], Johan Zetterqvist [ctb], Peter Strom [ctb], Benedicte Delcoigne [ctb], Mark Clements [aut, cre]
Maintainer: Mark Clements <mark.clements@ki.se>

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Package WhiteStripe updated to version 2.5.0 with previous version 2.4.3 dated 2024-05-09

Title: White Matter Normalization for Magnetic Resonance Images
Description: Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008> introduced 'WhiteStripe', an intensity-based normalization of T1 and T2 images, where normal appearing white matter performs well, but requires segmentation. This method performs white matter mean and standard deviation estimates on data that has been rigidly-registered to the 'MNI' template and uses histogram-based methods.
Author: R. Taki Shinohara [aut], John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

Diff between WhiteStripe versions 2.4.3 dated 2024-05-09 and 2.5.0 dated 2025-07-23

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Permanent link

Package TidyDensity updated to version 1.5.1 with previous version 1.5.0 dated 2024-05-28

Title: Functions for Tidy Analysis and Generation of Random Data
Description: To make it easy to generate random numbers based upon the underlying stats distribution functions. All data is returned in a tidy and structured format making working with the data simple and straight forward. Given that the data is returned in a tidy 'tibble' it lends itself to working with the rest of the 'tidyverse'.
Author: Steven Sanderson [aut, cre, cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>

Diff between TidyDensity versions 1.5.0 dated 2024-05-28 and 1.5.1 dated 2025-07-23

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 NEWS.md                                                     |   12 
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More information about TidyDensity at CRAN
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Package statar updated to version 0.7.7 with previous version 0.7.6 dated 2023-08-19

Title: Tools Inspired by 'Stata' to Manipulate Tabular Data
Description: A set of tools inspired by 'Stata' to explore data.frames ('summarize', 'tabulate', 'xtile', 'pctile', 'binscatter', elapsed quarters/month, lead/lag).
Author: Matthieu Gomez [aut, cre]
Maintainer: Matthieu Gomez <mg3901@columbia.edu>

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Package SensoMineR updated to version 1.28 with previous version 1.27 dated 2023-11-28

Title: Sensory Data Analysis
Description: Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).
Author: Francois Husson [aut, cre] , Sebastien Le [aut], Marine Cadoret [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package reactRouter updated to version 0.1.1 with previous version 0.1.0 dated 2025-04-29

Title: 'React Router' for 'shiny' Apps and 'Quarto'
Description: You can easily share url pages using 'React Router' in 'shiny' applications and 'Quarto' documents. The package wraps the 'react-router-dom' 'React' library and provides access to hash routing to navigate on multiple url pages.
Author: Felix Luginbuhl [aut, cre] , Andryas Waurzenczak [ctb], Shopify Inc. [ctb, cph]
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>

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Package R2WinBUGS updated to version 2.1-23 with previous version 2.1-22.1 dated 2024-02-05

Title: Running 'WinBUGS' and 'OpenBUGS' from 'R' / 'S-PLUS'
Description: Invoke a 'BUGS' model in 'OpenBUGS' or 'WinBUGS', a class "bugs" for 'BUGS' results and functions to work with that class. Function write.model() allows a 'BUGS' model file to be written. The class and auxiliary functions could be used with other MCMC programs, including 'JAGS'. The suggested package 'BRugs' (only needed for function openbugs()) is only available from the CRAN archives, see <https://cran.r-project.org/package=BRugs>.
Author: Andrew Gelman [aut], Sibylle Sturtz [aut], Uwe Ligges [cre, aut], Gregor Gorjanc [ctb], Jouni Kerman [ctb], Insightful Corp. [ctb]
Maintainer: Uwe Ligges <ligges@statistik.tu-dortmund.de>

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Package nltm updated to version 1.4.6 with previous version 1.4.5 dated 2023-12-03

Title: Non-Linear Transformation Models
Description: Fits a non-linear transformation model ('nltm') for analyzing survival data, see Tsodikov (2003) <doi:10.1111/1467-9868.00414>. The class of 'nltm' includes the following currently supported models: Cox proportional hazard, proportional hazard cure, proportional odds, proportional hazard - proportional hazard cure, proportional hazard - proportional odds cure, Gamma frailty, and proportional hazard - proportional odds.
Author: Gilda Garibotti [aut], Alexander Tsodikov [aut], Mark Clements [aut, cre]
Maintainer: Mark Clements <mark.clements@ki.se>

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Package FactoMineR updated to version 2.12 with previous version 2.11 dated 2024-04-20

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Author: Francois Husson [aut, cre] , Julie Josse [aut], Sebastien Le [aut], Jeremy Mazet [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package emdbook updated to version 1.3.14 with previous version 1.3.13 dated 2023-07-03

Title: Support Functions and Data for "Ecological Models and Data"
Description: Auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).
Author: Ben Bolker [aut, cre], Sang Woo Park [ctb], James Vonesh [dtc], Jacqueline Wilson [dtc], Russ Schmitt [dtc], Sally Holbrook [dtc], James D. Thomson [dtc], R. Scot Duncan [dtc]
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package BoundaryStats updated to version 2.3.0 with previous version 2.2.0 dated 2024-10-25

Title: Boundary Overlap Statistics
Description: Analysis workflow for finding geographic boundaries of ecological or landscape traits and comparing the placement of geographic boundaries of two traits. If data are trait values, trait data are transformed to boundary intensities based on approximate first derivatives across latitude and longitude. The package includes functions to create custom null models based on the input data. The boundary statistics are described in: Fortin, Drapeau, and Jacquez (1996) <doi:10.2307/3545584>.
Author: Amy Luo [aut, cre, cph] , Elizabeth Derryberry [ths]
Maintainer: Amy Luo <amy.luo.15@gmail.com>

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Package TPAC updated to version 0.3.0 with previous version 0.2.0 dated 2023-10-26

Title: Tissue-Adjusted Pathway Analysis of Cancer (TPAC)
Description: Contains logic for single sample gene set testing of cancer transcriptomic data with adjustment for normal tissue-specificity. Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.
Author: H. Robert Frost [aut, cre]
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>

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Package Rtumblr updated to version 0.1.1 with previous version 0.1.0 dated 2023-04-05

Title: Collecting and Analyzing 'Tumblr' Data
Description: An implementation of calls designed to collect 'Tumblr' data via its Application Program Interfaces (API), which can be found at the following URL: <https://www.tumblr.com/docs/en/api/v2>.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david@schochastics.net>

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Package rlibkriging updated to version 0.9-2.1 with previous version 0.9-2 dated 2025-07-22

Title: Kriging Models using the 'libKriging' Library
Description: Interface to 'libKriging' 'C++' library <https://github.com/libKriging> that should provide most standard Kriging / Gaussian process regression features (like in 'DiceKriging', 'kergp' or 'RobustGaSP' packages). 'libKriging' relies on Armadillo linear algebra library (Apache 2 license) by Conrad Sanderson, 'lbfgsb_cpp' is a 'C++' port around by Pascal Have of 'lbfgsb' library (BSD-3 license) by Ciyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales used for hyperparameters optimization.
Author: Yann Richet [aut, cre] , Pascal Have [aut], Yves Deville [aut], Conrad Sanderson [ctb], Ciyou Zhu [ctb], Richard Byrd [ctb], Jorge Nocedal [ctb], Jose Luis Morales [ctb], Mike Smith [ctb]
Maintainer: Yann Richet <yann.richet@irsn.fr>

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Package randomMachines updated to version 0.1.1 with previous version 0.1.0 dated 2023-12-14

Title: An Ensemble Modeling using Random Machines
Description: A novel ensemble method employing Support Vector Machines (SVMs) as base learners. This powerful ensemble model is designed for both classification (Ara A., et. al, 2021) <doi:10.6339/21-JDS1014>, and regression (Ara A., et. al, 2021) <doi:10.1016/j.eswa.2022.117107> problems, offering versatility and robust performance across different datasets and compared with other consolidated methods as Random Forests (Maia M, et. al, 2021) <doi:10.6339/21-JDS1025>.
Author: Mateus Maia [aut, cre] , Anderson Ara [cte] , Gabriel Ribeiro [cte]
Maintainer: Mateus Maia <mateus.maiamarques@glasgow.ac.uk>

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Package fat2Lpoly updated to version 1.2.6 with previous version 1.2.5 dated 2022-01-04

Title: Two-Locus Family-Based Association Test with Polytomous Outcome
Description: Performs family-based association tests with a polytomous outcome under 2-locus and 1-locus models defined by some design matrix.
Author: Alexandre Bureau [aut, cre], Jordie Croteau [aut]
Maintainer: Alexandre Bureau <alexandre.bureau@msp.ulaval.ca>

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Package factorplot updated to version 1.2.4 with previous version 1.2.3 dated 2024-05-23

Title: Presenting Pairwise Comparisons
Description: The tools herein calculate, print, summarize and plot pairwise differences that result from generalized linear models, general linear hypothesis tests and multinomial logistic regression models. For more information, see Armstrong (2013) <doi:10.32614/RJ-2013-021>.
Author: Dave Armstrong [aut, cre]
Maintainer: Dave Armstrong <davearmstrong.ps@gmail.com>

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Package errorlocate updated to version 1.1.2 with previous version 1.1.1 dated 2023-09-30

Title: Locate Errors with Validation Rules
Description: Errors in data can be located and removed using validation rules from package 'validate'. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, chapter 7.
Author: Edwin de Jonge [aut, cre] , Mark van der Loo [aut]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

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Package vcr updated to version 2.0.0 with previous version 1.7.0 dated 2025-03-10

Title: Record 'HTTP' Calls to Disk
Description: Record test suite 'HTTP' requests and replays them during future runs. A port of the Ruby gem of the same name (<https://github.com/vcr/vcr/>). Works by recording real 'HTTP' requests/responses on disk in 'cassettes', and then replaying matching responses on subsequent requests.
Author: Scott Chamberlain [aut, cre] , Aaron Wolen [aut] , Maelle Salmon [aut] , Daniel Possenriede [aut] , Hadley Wickham [aut], rOpenSci [fnd]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Permanent link

Package tatoo updated to version 1.1.3 with previous version 1.1.2 dated 2023-03-26

Title: Combine and Export Data Frames
Description: Functions to combine data.frames in ways that require additional effort in base R, and to add metadata (id, title, ...) that can be used for printing and xlsx export. The 'Tatoo_report' class is provided as a convenient helper to write several such tables to a workbook, one table per worksheet. Tatoo is built on top of 'openxlsx', but intimate knowledge of that package is not required to use tatoo.
Author: Stefan Fleck [aut, cre]
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between tatoo versions 1.1.2 dated 2023-03-26 and 1.1.3 dated 2025-07-23

 DESCRIPTION                       |   39 ++---
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More information about tatoo at CRAN
Permanent link

Package qlcMatrix updated to version 0.9.9 with previous version 0.9.8 dated 2024-05-08

Title: Utility Sparse Matrix Functions for Quantitative Language Comparison
Description: Extension of the functionality of the 'Matrix' package for using sparse matrices. Some of the functions are very general, while other are highly specific for special data format as used for quantitative language comparison.
Author: Michael Cysouw [aut, cre]
Maintainer: Michael Cysouw <cysouw@mac.com>

Diff between qlcMatrix versions 0.9.8 dated 2024-05-08 and 0.9.9 dated 2025-07-23

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More information about qlcMatrix at CRAN
Permanent link

Package gfunctions updated to version 1.1 with previous version 1.0 dated 2024-04-17

Title: G-Functions
Description: Modified versions of the lag() and summary() functions: glag() and gsummary(). The prefix 'g' is a reminder of who to blame if things do not work as they should.
Author: Genaro Sucarrat [aut, cre]
Maintainer: Genaro Sucarrat <gsucarrat@gmail.com>

Diff between gfunctions versions 1.0 dated 2024-04-17 and 1.1 dated 2025-07-23

 DESCRIPTION               |   14 ++++++++------
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More information about gfunctions at CRAN
Permanent link

Package crul updated to version 1.6.0 with previous version 1.5.0 dated 2024-07-19

Title: HTTP Client
Description: A simple HTTP client, with tools for making HTTP requests, and mocking HTTP requests. The package is built on R6, and takes inspiration from Ruby's 'faraday' gem (<https://rubygems.org/gems/faraday>). The package name is a play on curl, the widely used command line tool for HTTP, and this package is built on top of the R package 'curl', an interface to 'libcurl' (<https://curl.se/libcurl/>).
Author: Scott Chamberlain [aut, cre]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between crul versions 1.5.0 dated 2024-07-19 and 1.6.0 dated 2025-07-23

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New package RDML with initial version 1.1
Package: RDML
Title: Importing Real-Time Thermo Cycler (qPCR) Data from RDML Format Files
Version: 1.1
Date: 2025-07-09
Description: Imports real-time thermo cycler (qPCR) data from Real-time PCR Data Markup Language (RDML) and transforms to the appropriate formats of the 'qpcR' and 'chipPCR' packages, as described in Rodiger et al. (2017) <doi:10.1093/bioinformatics/btx528>. Contains a dendrogram visualization for the structure of RDML object and GUI for RDML editing.
License: MIT + file LICENSE
URL: https://github.com/PCRuniversum/RDML
Depends: R (>= 3.2.0)
Imports: checkmate (>= 1.6.2), data.table, pipeR, readxl, rlist (>= 0.4), R6 (>= 2.0.1), stringr, tools (>= 3.2), xml2 (>= 1.0), lubridate (>= 1.6.0)
Suggests: chipPCR, magrittr, reshape2, qpcR, dplyr, ggplot2, knitr, kfigr, MBmca, shiny, shinyjs, shinythemes, V8, testthat
NeedsCompilation: no
Packaged: 2025-07-23 11:10:57 UTC; blagodatskih
Maintainer: Konstantin Blagodatskikh <k.blag@yandex.ru>
Repository: CRAN
Date/Publication: 2025-07-23 11:50:08 UTC
Author: Konstantin Blagodatskikh [cre, aut], Stefan Roediger [aut], Michal Burdukiewicz [aut] , Andrej-Nikolai Spiess [aut]

More information about RDML at CRAN
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Package rater updated to version 1.3.2 with previous version 1.3.1 dated 2023-09-11

Title: Statistical Models of Repeated Categorical Rating Data
Description: Fit statistical models based on the Dawid-Skene model - Dawid and Skene (1979) <doi:10.2307/2346806> - to repeated categorical rating data. Full Bayesian inference for these models is supported through the Stan modelling language. 'rater' also allows the user to extract and plot key parameters of these models.
Author: Jeffrey Pullin [aut, cre, cph] , Damjan Vukcevic [aut] , Lars Moelgaard Saxhaug [ctb]
Maintainer: Jeffrey Pullin <jeffrey.pullin@gmail.com>

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Package MLGL updated to version 1.0.1 with previous version 1.0.0 dated 2023-03-15

Title: Multi-Layer Group-Lasso
Description: It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2023) <doi:10.18637/jss.v106.i03>).
Author: Quentin Grimonprez [aut, cre], Samuel Blanck [ctb], Alain Celisse [ths], Guillemette Marot [ths], Yi Yang [ctb], Hui Zou [ctb]
Maintainer: Quentin Grimonprez <quentingrim@yahoo.fr>

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Package lgrExtra updated to version 0.2.0 with previous version 0.1.1 dated 2025-07-09

Title: Extra Appenders for 'lgr'
Description: Additional appenders for the logging package 'lgr' that support logging to 'Elasticsearch', 'Dynatrace', 'AWSCloudWatchLog', databases, 'syslog', email- and push notifications, and more.
Author: Stefan Fleck [aut, cre] , Jimmy Briggs [ctb, rev]
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

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Package AgePopDenom updated to version 1.2.3 with previous version 1.2.2 dated 2025-07-22

Title: Model Fine-Scale Age-Structured Population Data using Open-Source Data
Description: Automate the modelling of age-structured population data using survey data, grid population estimates and urban-rural extents.
Author: Mohamed A. Yusuf [aut, cre] , Victor A. Alegana [aut] , Chibuzor Christopher Nnanatu [aut] , Andrew Tatem [aut]
Maintainer: Mohamed A. Yusuf <moyusuf@who.int>

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Package scGate updated to version 1.7.2 with previous version 1.7.0 dated 2025-04-24

Title: Marker-Based Cell Type Purification for Single-Cell Sequencing Data
Description: A common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. 'scGate' automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. Briefly, 'scGate' takes as input: i) a gene expression matrix stored in a 'Seurat' object and ii) a “gating model” (GM), consisting of a set of marker genes that define the cell population of interest. The GM can be as simple as a single marker gene, or a combination of positive and negative markers. More complex GMs can be constructed in a hierarchical fashion, akin to gating strategies employed in flow cytometry. 'scGate' evaluates the strength of signature marker expression in each cell using the rank-based method 'UCell', and then performs k-nearest neighbor (kNN) smoothing by calculating the mean 'UCell' score across neighboring cells. kNN-smoothing aims at compensating for the large degree of s [...truncated...]
Author: Massimo Andreatta [aut, cre] , Ariel Berenstein [aut] , Josep Garnica [aut], Santiago Carmona [aut]
Maintainer: Massimo Andreatta <massimo.andreatta@unige.ch>

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Package REEMtree updated to version 0.90.6 with previous version 0.90.5 dated 2023-10-24

Title: Regression Trees with Random Effects for Longitudinal (Panel) Data
Description: A data mining approach for longitudinal and clustered data, which combines the structure of mixed effects model with tree-based estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM trees: a data mining approach for longitudinal and clustered data <doi:10.1007/s10994-011-5258-3>.
Author: Rebecca Sela [aut], Jeffrey Simonoff [aut], Wenbo Jing [ctb, cre]
Maintainer: Wenbo Jing <wj2093@stern.nyu.edu>

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Package GPCMlasso updated to version 0.1-8 with previous version 0.1-7 dated 2024-01-23

Title: Differential Item Functioning in Generalized Partial Credit Models
Description: Provides a framework to detect Differential Item Functioning (DIF) in Generalized Partial Credit Models (GPCM) and special cases of the GPCM as proposed by Schauberger and Mair (2019) <doi:10.3758/s13428-019-01224-2>. A joint model is set up where DIF is explicitly parametrized and penalized likelihood estimation is used for parameter selection. The big advantage of the method called GPCMlasso is that several variables can be treated simultaneously and that both continuous and categorical variables can be used to detect DIF.
Author: Gunther Schauberger [aut, cre]
Maintainer: Gunther Schauberger <gunther.schauberger@tum.de>

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Package geonetwork updated to version 0.6.0 with previous version 0.5.0 dated 2023-04-14

Title: Geographic Networks
Description: Provides classes and methods for handling networks or graphs whose nodes are geographical (i.e. locations in the globe). The functionality includes the creation of objects of class geonetwork as a graph with node coordinates, the computation of network measures, the support of spatial operations (projection to different Coordinate Reference Systems, handling of bounding boxes, etc.) and the plotting of the geonetwork object combined with supplementary cartography for spatial representation.
Author: Facundo Munoz [aut, cre]
Maintainer: Facundo Munoz <facundo.munoz@cirad.fr>

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Package bnRep updated to version 0.0.5 with previous version 0.0.4 dated 2025-05-24

Title: A Repository of Bayesian Networks from the Academic Literature
Description: A collection of Bayesian networks (discrete, Gaussian, and conditional linear Gaussian) collated from recent academic literature. The 'bnRep_summary' object provides an overview of the Bayesian networks in the repository and the package documentation includes details about the variables in each network. A Shiny app to explore the repository can be launched with 'bnRep_app()' and is available online at <https://manueleleonelli.shinyapps.io/bnRep>. Reference: 'M. Leonelli' (2025) <doi:10.1016/j.neucom.2025.129502>.
Author: Manuele Leonelli [aut, cre, cph]
Maintainer: Manuele Leonelli <manuele.leonelli@ie.edu>

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Package ebreg (with last version 0.1.3) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2021-05-26 0.1.3
2020-05-26 0.1.2
2020-05-21 0.1.1
2019-10-29 0.1.0

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Package SCIntRuler (with last version 0.99.6) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2024-07-12 0.99.6

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Package CIDER (with last version 0.99.4) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2025-02-07 0.99.4

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Package UPCM updated to version 0.0-4 with previous version 0.0-3 dated 2021-04-27

Title: Uncertainty in Partial Credit Models
Description: Provides an extension to the Partial Credit Model and Generalized Partial Credit Models which allows for an additional person parameter that characterizes the uncertainty of the person. The method was originally proposed by Tutz and Schauberger (2020) <doi:10.1177/0146621620920932>.
Author: Gunther Schauberger [aut, cre]
Maintainer: Gunther Schauberger <gunther.schauberger@tum.de>

Diff between UPCM versions 0.0-3 dated 2021-04-27 and 0.0-4 dated 2025-07-23

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Package SpatialPosition updated to version 2.1.3 with previous version 2.1.2 dated 2023-09-14

Title: Spatial Position Models
Description: Computes spatial position models: the potential model as defined by Stewart (1941) <doi:10.1126/science.93.2404.89> and catchment areas as defined by Reilly (1931) or Huff (1964) <doi:10.2307/1249154>.
Author: Timothee Giraud [cre, aut] , Hadrien Commenges [aut], Joel Boulier [ctb]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>

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Package rcartocolor updated to version 2.1.2 with previous version 2.1.1 dated 2023-05-13

Title: 'CARTOColors' Palettes
Description: Provides color schemes for maps and other graphics designed by 'CARTO' as described at <https://carto.com/carto-colors/>. It includes four types of palettes: aggregation, diverging, qualitative, and quantitative.
Author: Jakub Nowosad [aut, cre]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package cheapr updated to version 1.3.2 with previous version 1.3.1 dated 2025-06-03

Title: Simple Functions to Save Time and Memory
Description: Fast and memory-efficient (or 'cheap') tools to facilitate efficient programming, saving time and memory. It aims to provide 'cheaper' alternatives to common base R functions, as well as some additional functions.
Author: Nick Christofides [aut, cre]
Maintainer: Nick Christofides <nick.christofides.r@gmail.com>

Diff between cheapr versions 1.3.1 dated 2025-06-03 and 1.3.2 dated 2025-07-23

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Package Statamarkdown (with last version 0.9.2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2023-12-04 0.9.2
2023-06-01 0.8.0
2023-05-25 0.7.4
2023-02-15 0.7.2

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Package oceanmap (with last version 0.1.6) was removed from CRAN

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2023-11-10 0.1.6
2023-10-19 0.1.5

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Package SASmarkdown (with last version 0.8.2) was removed from CRAN

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2023-03-10 0.8.2
2023-02-03 0.8.1
2022-09-20 0.8.0
2022-08-16 0.7.2
2017-11-30 0.4.3
2017-07-10 0.3.3

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Package MixSemiRob (with last version 1.1.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2023-09-20 1.1.0
2023-04-28 1.0.0

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Package MTest (with last version 1.0.2) was removed from CRAN

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2023-10-06 1.0.2
2023-09-20 1.0.1
2023-07-18 1.0.0

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Package RchivalTag (with last version 0.1.9) was removed from CRAN

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2023-11-10 0.1.9
2023-10-20 0.1.8

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Package clusEvol (with last version 1.0.0) was removed from CRAN

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2024-02-26 1.0.0

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Package civis (with last version 3.1.2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2023-03-31 3.1.2
2023-02-28 3.1.1
2023-02-22 3.1.0
2020-06-22 3.0.0
2020-02-24 2.1.2
2019-09-07 2.1.0
2019-06-19 2.0.0
2019-02-12 1.6.1
2018-08-15 1.5.1
2018-06-21 1.5.0
2018-05-06 1.4.0
2018-03-30 1.3.0
2018-01-23 1.2.0
2017-11-21 1.1.1
2017-11-09 1.1.0
2017-09-21 1.0.2
2017-09-19 1.0.1
2017-09-16 1.0.0

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Package JNplots (with last version 0.1.1) was removed from CRAN

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2023-11-24 0.1.1
2023-09-12 0.1.0

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Package ecpc (with last version 3.1.1) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2023-02-27 3.1.1
2022-05-13 3.1
2022-03-22 3.0
2021-05-03 2.0

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Package statgenQTLxT updated to version 1.0.3 with previous version 1.0.2 dated 2024-01-23

Title: Multi-Trait and Multi-Trial Genome Wide Association Studies
Description: Fast multi-trait and multi-trail Genome Wide Association Studies (GWAS) following the method described in Zhou and Stephens. (2014), <doi:10.1038/nmeth.2848>. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.
Author: Bart-Jan van Rossum [aut, cre] , Willem Kruijer [aut] , Fred van Eeuwijk [ctb] , Martin P Boer [ctb] , Daniela Bustos-Korts [ctb] , Emilie J Millet [ctb] , Joao Paulo [ctb] , Maikel Verouden [ctb] , Ron Wehrens [ctb] , Choazhi Zheng [ctb]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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New package libopenexr with initial version 3.4.0-4
Package: libopenexr
Title: Static Library and Headers for 'OpenEXR' Image I/O
Version: 3.4.0-4
Description: Provides the 'OpenEXR' static library and 'C++' headers for high-dynamic-range image I/O (see <https://openexr.com/>) needed to link R packages against the 'OpenEXR' library, along with a basic R interface to load 'EXR' images.
Depends: R (>= 4.3.0)
License: BSD_3_clause + file LICENSE
LinkingTo: libimath, libdeflate
Encoding: UTF-8
LazyData: true
SystemRequirements: CMake, GNU make
Biarch: TRUE
BugReports: https://github.com/tylermorganwall/libopenexr/issues
NeedsCompilation: yes
Packaged: 2025-07-22 02:23:18 UTC; tyler
Author: Tyler Morgan-Wall [aut, cre] , Aaron Demolder [ctb, cph], Abe Fettig [ctb, cph], Aloys Baillet [ctb, cph], Andre Mazzone [ctb, cph], Andrew Kunz [ctb, cph], Anton Dukhovnikov [ctb, cph], Antonio Rojas [ctb, cph], Aras Pranckevicius [ctb, cph], Arkady [...truncated...]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-23 08:10:02 UTC

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Package IPEC updated to version 1.1.1 with previous version 1.1.0 dated 2024-01-13

Title: Root Mean Square Curvature Calculation
Description: Calculates the RMS intrinsic and parameter-effects curvatures of a nonlinear regression model. The curvatures are global measures of assessing whether a model/data set combination is close-to-linear or not. See Bates and Watts (1980) <doi:10.1002/9780470316757> and Ratkowsky and Reddy (2017) <doi:10.1093/aesa/saw098> for details.
Author: Peijian Shi [aut, cre], Peter M. Ridland [aut], David A. Ratkowsky [aut], Yang Li [aut]
Maintainer: Peijian Shi <pjshi@njfu.edu.cn>

Diff between IPEC versions 1.1.0 dated 2024-01-13 and 1.1.1 dated 2025-07-23

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Package gpboost updated to version 1.6.1 with previous version 1.6.0 dated 2025-07-22

Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2022, JMLR) <https://www.jmlr.org/papers/v23/20-322.html> and Sigrist (2023, TPAMI) <doi:10.1109/TPAMI.2022.3168152> for more information on the methodology.
Author: Fabio Sigrist [aut, cre], Tim Gyger [aut], Pascal Kuendig [aut], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the incl [...truncated...]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>

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Package GLDreg updated to version 1.1.2 with previous version 1.1.1 dated 2024-01-22

Title: Fit GLD Regression/Quantile/AFT Model to Data
Description: Owing to the rich shapes of Generalised Lambda Distributions (GLDs), GLD standard/quantile/Accelerated Failure Time (AFT) regression is a competitive flexible model compared to standard/quantile/AFT regression. The proposed method has some major advantages: 1) it provides a reference line which is very robust to outliers with the attractive property of zero mean residuals and 2) it gives a unified, elegant quantile regression model from the reference line with smooth regression coefficients across different quantiles. For AFT model, it also eliminates the needs to try several different AFT models, owing to the flexible shapes of GLD. The goodness of fit of the proposed model can be assessed via QQ plots and Kolmogorov-Smirnov tests and data driven smooth test, to ensure the appropriateness of the statistical inference under consideration. Statistical distributions of coefficients of the GLD regression line are obtained using simulation, and interval estimates are obtained directly fro [...truncated...]
Author: Steve Su [aut, cre, cph] , R Core Team [aut]
Maintainer: Steve Su <allegro.su@gmail.com>

Diff between GLDreg versions 1.1.1 dated 2024-01-22 and 1.1.2 dated 2025-07-23

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Package GLDEX updated to version 2.0.0.9.4 with previous version 2.0.0.9.3 dated 2023-08-21

Title: Fitting Single and Mixture of Generalised Lambda Distributions
Description: The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution. References include the following: Karvanen and Nuutinen (2008) "Characterizing the generalized lambda distribution by L-moments" <doi:10.1016/j.csda.2007.06.021>, King and MacGillivray (1999) "A starship method for fitting the generalised lambda distributions" <doi:10.1111/1467-842X.00089>, Su (2005) "A Discretized Approach to Flexibly Fit Generalized Lambda Distribut [...truncated...]
Author: Steve Su [aut, cre, cph] , Martin Maechler [aut], Juha Karvanen [aut], Robert King [aut], Benjamin Dean [ctb], R Core Team [aut]
Maintainer: Steve Su <allegro.su@gmail.com>

Diff between GLDEX versions 2.0.0.9.3 dated 2023-08-21 and 2.0.0.9.4 dated 2025-07-23

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Package cartography updated to version 3.1.5 with previous version 3.1.4 dated 2023-09-14

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package helps to design cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features that improve the graphic presentation of maps, for instance, map palettes, layout elements (scale, north arrow, title...), labels or legends. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
Author: Timothee Giraud [cre, aut] , Nicolas Lambert [aut], Diego Hernangomez [ctb] , Ian Fellows [cph]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>

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Package Tivy updated to version 0.1.1 with previous version 0.1.0 dated 2025-07-22

Title: Toolkit for Investigation and Visualization of Young Anchovies
Description: Specialized toolkit for processing biological and fisheries data from Peru's anchovy (Engraulis ringens) fishery. Provides functions to analyze fishing logbooks, calculate biological indicators (length-weight relationships, juvenile percentages), generate spatial fishing indicators, and visualize regulatory measures from Peru's Ministry of Production. Features automated data processing from multiple file formats, coordinate validation, spatial analysis of fishing zones, and tools for analyzing fishing closure announcements and regulatory compliance. Includes built-in datasets of Peruvian coastal coordinates and parallel lines for analyzing fishing activities within regulatory zones.
Author: Hans Ttito [aut, cre]
Maintainer: Hans Ttito <kvttitos@gmail.com>

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Package spsComps updated to version 0.3.4.0 with previous version 0.3.3.0 dated 2023-07-12

Title: 'systemPipeShiny' UI and Server Components
Description: The systemPipeShiny (SPS) framework comes with many UI and server components. However, installing the whole framework is heavy and takes some time. If you would like to use UI and server components from SPS in your own Shiny apps, do not hesitate to try this package.
Author: Le Zhang [aut, cre]
Maintainer: Le Zhang <lezhang100@gmail.com>

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Package rMVP updated to version 1.4.5 with previous version 1.4.0 dated 2025-01-22

Title: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool
Description: A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. 'rMVP' contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and 'SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/ [...truncated...]
Author: Lilin Yin [aut], Haohao Zhang [aut], Zhenshuang Tang [aut], Jingya Xu [aut], Dong Yin [aut], Zhiwu Zhang [aut], Xiaohui Yuan [aut], Mengjin Zhu [aut], Shuhong Zhao [aut], Xinyun Li [aut], Qishan Wang [ctb], Feng Tian [ctb], Hyunmin Kang [ctb], Xiang [...truncated...]
Maintainer: Xiaolei Liu <xll198708@gmail.com>

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Package rashnu updated to version 0.1.2 with previous version 0.1.1 dated 2025-06-18

Title: Balanced Sample Size and Power Calculation Tools
Description: Implements sample size and power calculation methods with a focus on balance and fairness in study design, inspired by the Zoroastrian deity Rashnu, the judge who weighs truth. Supports survival analysis and various hypothesis testing frameworks.
Author: Sungho Choi [aut], Gyeom Hwangbo [ctb, cre], Zarathu [cph, fnd]
Maintainer: Gyeom Hwangbo <hbgyeom@gmail.com>

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Package polyglotr updated to version 1.7.0 with previous version 1.6.1 dated 2025-07-09

Title: Translate Text
Description: Provide easy methods to translate pieces of text. Functions send requests to translation services online.
Author: Tomer Iwan [aut, cre, cph]
Maintainer: Tomer Iwan <t.iwan@vu.nl>

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Package geeasy updated to version 0.1.3 with previous version 0.1.2 dated 2024-04-29

Title: Solve Generalized Estimating Equations for Clustered Data
Description: Estimation of generalized linear models with correlated/clustered observations by use of generalized estimating equations (GEE). See e.g. Halekoh and Højsgaard, (2005, <doi:10.18637/jss.v015.i02>), for details. Several types of clustering are supported, including exchangeable variance structures, AR1 structures, M-dependent, user-specified variance structures and more. The model fitting computations are performed using modified code from the 'geeM' package, while the interface and output objects have been written to resemble the 'geepack' package. The package also contains additional tools for working with and inspecting results from the 'geepack' package, e.g. a 'confint' method for 'geeglm' objects from 'geepack'.
Author: Anne Helby Petersen [aut], Lee McDaniel [aut] , Claus Ekstroem [ctb] , Soeren Hoejsgaard [aut, cre]
Maintainer: Soeren Hoejsgaard <sorenh@math.aau.dk>

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Package lgr updated to version 0.5.0 with previous version 0.4.4 dated 2022-09-05

Title: A Fully Featured Logging Framework
Description: A flexible, feature-rich yet light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, 'JSON', (rotating) files, memory buffers. For extra appenders that support logging to databases, email and push notifications see the the package lgr.app.
Author: Stefan Fleck [aut, cre]
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between lgr versions 0.4.4 dated 2022-09-05 and 0.5.0 dated 2025-07-23

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Package spatstat.model updated to version 3.4-0 with previous version 3.3-6 dated 2025-05-22

Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
Description: Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope t [...truncated...]
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb, cph], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao [...truncated...]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.model versions 3.3-6 dated 2025-05-22 and 3.4-0 dated 2025-07-23

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Package sasLM updated to version 0.10.6 with previous version 0.10.5 dated 2024-10-02

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, TTEST, FREQ, and UNIVARIATE. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).
Author: Kyun-Seop Bae [aut, cre]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between sasLM versions 0.10.5 dated 2024-10-02 and 0.10.6 dated 2025-07-23

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Package influence.SEM updated to version 2.4 with previous version 2.3 dated 2022-05-11

Title: Case Influence in Structural Equation Models
Description: A set of tools for evaluating several measures of case influence for structural equation models.
Author: Massimiliano Pastore [aut, cre], Gianmarco Altoe' [ctb]
Maintainer: Massimiliano Pastore <massimiliano.pastore@unipd.it>

Diff between influence.SEM versions 2.3 dated 2022-05-11 and 2.4 dated 2025-07-23

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Package AcceptanceSampling updated to version 1.0.11 with previous version 1.0-10 dated 2023-12-06

Title: Creation and Evaluation of Acceptance Sampling Plans
Description: Provides functionality for creating and evaluating acceptance sampling plans. Sampling plans can be single, double or multiple.
Author: Andreas Kiermeier [aut, cre], Peter Bloomfield [ctb]
Maintainer: Andreas Kiermeier <Andreas.Kiermeier@gmail.com>

Diff between AcceptanceSampling versions 1.0-10 dated 2023-12-06 and 1.0.11 dated 2025-07-23

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