Thu, 09 May 2024

Package WhiteStripe updated to version 2.4.3 with previous version 2.4.2 dated 2022-08-30

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 2.4.2 dated 2022-08-30 and 2.4.3 dated 2024-05-09

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Package gsMAMS updated to version 0.7.2 with previous version 0.7.1 dated 2023-05-04

Title: Group Sequential Designs of Multi-Arm Multi-Stage Trials
Description: It provides functions to generate operating characteristics and to calculate Sequential Conditional Probability Ratio Tests(SCPRT) efficacy and futility boundary values along with sample/event size of Multi-Arm Multi-Stage(MAMS) trials for different outcomes. The package is based on Jianrong Wu, Yimei Li, Liang Zhu (2023) <doi:10.1002/sim.9682>, Jianrong Wu, Yimei Li (2023) "Group Sequential Multi-Arm Multi-Stage Survival Trial Design with Treatment Selection"(Manuscript accepted for publication) and Jianrong Wu, Yimei Li, Shengping Yang (2023) "Group Sequential Multi-Arm Multi-Stage Trial Design with Ordinal Endpoints"(In preparation).
Author: Tushar Patni [aut, cre], Yimei Li [aut], Jianrong Wu [aut]
Maintainer: Tushar Patni <tushar.patni006@gmail.com>

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More information about gsMAMS at CRAN
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Package ftExtra updated to version 0.6.4 with previous version 0.6.3 dated 2024-04-02

Title: Extensions for 'Flextable'
Description: Build display tables easily by extending the functionality of the 'flextable' package. Features include spanning header, grouping rows, parsing markdown and so on.
Author: Atsushi Yasumoto [aut, cph, cre] , David Gohel [ctb], Romain Francois [ctb] , Tatsuya Shima [ctb]
Maintainer: Atsushi Yasumoto <atusy.rpkg@gmail.com>

Diff between ftExtra versions 0.6.3 dated 2024-04-02 and 0.6.4 dated 2024-05-09

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Package transport updated to version 0.15-2 with previous version 0.15-0 dated 2024-03-26

Title: Computation of Optimal Transport Plans and Wasserstein Distances
Description: Solve optimal transport problems. Compute Wasserstein distances (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, (weighted) point patterns, and mass vectors.
Author: Dominic Schuhmacher [aut, cre], Bjoern Baehre [aut] , Nicolas Bonneel [aut] , Carsten Gottschlich [aut] , Valentin Hartmann [aut] , Florian Heinemann [aut] , Bernhard Schmitzer [aut] , Joern Schrieber [aut] , Timo Wilm [ctb]
Maintainer: Dominic Schuhmacher <dominic.schuhmacher@mathematik.uni-goettingen.de>

Diff between transport versions 0.15-0 dated 2024-03-26 and 0.15-2 dated 2024-05-09

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Package ExpImage updated to version 0.10.1 with previous version 0.10.0 dated 2024-05-03

Title: Analysis of Images in Experiments
Description: Tools created for image analysis in researches. There are functions associated with image editing, segmentation, and obtaining biometric measurements (Este pacote foi idealizado para para a analise de imagens em pesquisas. Ha funcoes associadas a edicao de imagens, segmentacao, e obtencao de medidas biometricas) <https://www.expstat.com/pacotes-do-r/expimage>.
Author: Alcinei Mistico Azevedo [aut, cre]
Maintainer: Alcinei Mistico Azevedo <alcineimistico@hotmail.com>

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Package loadeR updated to version 1.2.0 with previous version 1.1.8 dated 2024-02-08

Title: Load Data for Analysis System
Description: Provides a framework to load text and excel files through a 'shiny' graphical interface. It allows renaming, transforming, ordering and removing variables. It includes basic exploratory methods such as the mean, median, mode, normality test, histogram and correlation.
Author: Oldemar Rodriguez [aut, cre], Diego Jimenez [aut], Joseline Quiros [aut]
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

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Package volker updated to version 2.0.0 with previous version 1.0.2 dated 2024-02-22

Title: High-Level Functions for Tabulating, Charting and Reporting Survey Data
Description: Craft polished tables and plots in Markdown reports. Simply choose whether to treat your data as counts or metrics, and the package will automatically generate well-designed default tables and plots for you. Boiled down to the basics, with labeling features and simple interactive reports. All functions are 'tidyverse' compatible.
Author: Jakob Juenger [aut, cre, cph] , Henrieke Kotthoff [aut, ctb], Chantal Gaertner [ctb]
Maintainer: Jakob Juenger <jakob.juenger@uni-muenster.de>

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More information about volker at CRAN
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Package sits updated to version 1.5.0 with previous version 1.4.2-1 dated 2023-11-02

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, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, and Digital Earth Africa using the Spatio-temporal Asset Catalog (STAC) protocol (<https://stacspec.org/> and the 'gdalcubes' R package developed by Appel and Pebesma (2019) <doi:10.3390/data4030092>. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Includes functions for quality assessment of training samples using self-organized maps as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neu [...truncated...]
Author: Rolf Simoes [aut], Gilberto Camara [aut, cre], Felipe Souza [aut], Lorena Santos [aut], Pedro Andrade [aut], Karine Ferreira [aut], Alber Sanchez [aut], Gilberto Queiroz [aut]
Maintainer: Gilberto Camara <gilberto.camara.inpe@gmail.com>

Diff between sits versions 1.4.2-1 dated 2023-11-02 and 1.5.0 dated 2024-05-09

 sits-1.4.2-1/sits/R/api_imputation.R                                                                    |only
 sits-1.4.2-1/sits/inst/extdata/segment                                                                  |only
 sits-1.4.2-1/sits/src/sample_points.cpp                                                                 |only
 sits-1.4.2-1/sits/tests/testthat/Rplots.pdf                                                             |only
 sits-1.5.0/sits/DESCRIPTION                                                                             |   77 
 sits-1.5.0/sits/MD5                                                                                     |  483 +--
 sits-1.5.0/sits/NAMESPACE                                                                               |   81 
 sits-1.5.0/sits/NEWS.md                                                                                 |   33 
 sits-1.5.0/sits/R/RcppExports.R                                                                         |   96 
 sits-1.5.0/sits/R/api_accessors.R                                                                       |    2 
 sits-1.5.0/sits/R/api_accuracy.R                                                                        |   24 
 sits-1.5.0/sits/R/api_apply.R                                                                           |   57 
 sits-1.5.0/sits/R/api_band.R                                                                            |   24 
 sits-1.5.0/sits/R/api_bbox.R                                                                            |   22 
 sits-1.5.0/sits/R/api_block.R                                                                           |   14 
 sits-1.5.0/sits/R/api_check.R                                                                           | 1511 ++++------
 sits-1.5.0/sits/R/api_chunks.R                                                                          |   43 
 sits-1.5.0/sits/R/api_classify.R                                                                        |  317 +-
 sits-1.5.0/sits/R/api_clean.R                                                                           |   22 
 sits-1.5.0/sits/R/api_cluster.R                                                                         |   36 
 sits-1.5.0/sits/R/api_colors.R                                                                          |   66 
 sits-1.5.0/sits/R/api_combine_predictions.R                                                             |   28 
 sits-1.5.0/sits/R/api_comp.R                                                                            |   15 
 sits-1.5.0/sits/R/api_conf.R                                                                            |  512 +--
 sits-1.5.0/sits/R/api_csv.R                                                                             |   12 
 sits-1.5.0/sits/R/api_cube.R                                                                            |  328 +-
 sits-1.5.0/sits/R/api_data.R                                                                            |  165 -
 sits-1.5.0/sits/R/api_debug.R                                                                           |   18 
 sits-1.5.0/sits/R/api_download.R                                                                        |   82 
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 sits-1.5.0/sits/R/api_factory.R                                                                         |    2 
 sits-1.5.0/sits/R/api_file.R                                                                            |    2 
 sits-1.5.0/sits/R/api_file_info.R                                                                       |   16 
 sits-1.5.0/sits/R/api_gdal.R                                                                            |   47 
 sits-1.5.0/sits/R/api_gdalcubes.R                                                                       |  141 
 sits-1.5.0/sits/R/api_jobs.R                                                                            |    9 
 sits-1.5.0/sits/R/api_kohonen.R                                                                         |only
 sits-1.5.0/sits/R/api_label_class.R                                                                     |   52 
 sits-1.5.0/sits/R/api_merge.R                                                                           |only
 sits-1.5.0/sits/R/api_mixture_model.R                                                                   |   31 
 sits-1.5.0/sits/R/api_ml_model.R                                                                        |    2 
 sits-1.5.0/sits/R/api_mosaic.R                                                                          |   54 
 sits-1.5.0/sits/R/api_opensearch.R                                                                      |only
 sits-1.5.0/sits/R/api_parallel.R                                                                        |   34 
 sits-1.5.0/sits/R/api_period.R                                                                          |   17 
 sits-1.5.0/sits/R/api_plot_raster.R                                                                     |  517 +--
 sits-1.5.0/sits/R/api_plot_time_series.R                                                                |   36 
 sits-1.5.0/sits/R/api_plot_vector.R                                                                     |  145 
 sits-1.5.0/sits/R/api_point.R                                                                           |    8 
 sits-1.5.0/sits/R/api_predictors.R                                                                      |    2 
 sits-1.5.0/sits/R/api_raster.R                                                                          |  146 
 sits-1.5.0/sits/R/api_raster_sub_image.R                                                                |  106 
 sits-1.5.0/sits/R/api_raster_terra.R                                                                    |   50 
 sits-1.5.0/sits/R/api_reclassify.R                                                                      |   48 
 sits-1.5.0/sits/R/api_reduce.R                                                                          |only
 sits-1.5.0/sits/R/api_regularize.R                                                                      |  118 
 sits-1.5.0/sits/R/api_roi.R                                                                             |   19 
 sits-1.5.0/sits/R/api_s2tile.R                                                                          |  168 -
 sits-1.5.0/sits/R/api_samples.R                                                                         |   27 
 sits-1.5.0/sits/R/api_segments.R                                                                        |  397 +-
 sits-1.5.0/sits/R/api_select.R                                                                          |only
 sits-1.5.0/sits/R/api_sf.R                                                                              |  107 
 sits-1.5.0/sits/R/api_shp.R                                                                             |   66 
 sits-1.5.0/sits/R/api_signal.R                                                                          |   25 
 sits-1.5.0/sits/R/api_smooth.R                                                                          |    8 
 sits-1.5.0/sits/R/api_smote.R                                                                           |  102 
 sits-1.5.0/sits/R/api_som.R                                                                             |   33 
 sits-1.5.0/sits/R/api_source.R                                                                          |  253 -
 sits-1.5.0/sits/R/api_source_aws.R                                                                      |   38 
 sits-1.5.0/sits/R/api_source_bdc.R                                                                      |    4 
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 sits-1.5.0/sits/R/api_source_deafrica.R                                                                 |  186 +
 sits-1.5.0/sits/R/api_source_hls.R                                                                      |   74 
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 sits-1.5.0/sits/R/api_source_mpc.R                                                                      |  345 +-
 sits-1.5.0/sits/R/api_source_sdc.R                                                                      |   34 
 sits-1.5.0/sits/R/api_source_stac.R                                                                     |  159 -
 sits-1.5.0/sits/R/api_source_usgs.R                                                                     |  102 
 sits-1.5.0/sits/R/api_space_time_operations.R                                                           |    8 
 sits-1.5.0/sits/R/api_stac.R                                                                            |   74 
 sits-1.5.0/sits/R/api_summary.R                                                                         |   32 
 sits-1.5.0/sits/R/api_tibble.R                                                                          |   55 
 sits-1.5.0/sits/R/api_tile.R                                                                            |  219 +
 sits-1.5.0/sits/R/api_timeline.R                                                                        |  103 
 sits-1.5.0/sits/R/api_torch.R                                                                           |   41 
 sits-1.5.0/sits/R/api_torch_psetae.R                                                                    |   32 
 sits-1.5.0/sits/R/api_ts.R                                                                              |   74 
 sits-1.5.0/sits/R/api_uncertainty.R                                                                     |  128 
 sits-1.5.0/sits/R/api_utils.R                                                                           |   31 
 sits-1.5.0/sits/R/api_values.R                                                                          |   18 
 sits-1.5.0/sits/R/api_variance.R                                                                        |    6 
 sits-1.5.0/sits/R/api_vector.R                                                                          |    6 
 sits-1.5.0/sits/R/api_view.R                                                                            |  242 -
 sits-1.5.0/sits/R/sits_accuracy.R                                                                       |  210 -
 sits-1.5.0/sits/R/sits_active_learning.R                                                                |   20 
 sits-1.5.0/sits/R/sits_apply.R                                                                          |   69 
 sits-1.5.0/sits/R/sits_bands.R                                                                          |   41 
 sits-1.5.0/sits/R/sits_bbox.R                                                                           |    9 
 sits-1.5.0/sits/R/sits_classify.R                                                                       |  197 -
 sits-1.5.0/sits/R/sits_clean.R                                                                          |only
 sits-1.5.0/sits/R/sits_cluster.R                                                                        |   74 
 sits-1.5.0/sits/R/sits_colors.R                                                                         |  151 
 sits-1.5.0/sits/R/sits_combine_predictions.R                                                            |   27 
 sits-1.5.0/sits/R/sits_config.R                                                                         |   34 
 sits-1.5.0/sits/R/sits_csv.R                                                                            |   31 
 sits-1.5.0/sits/R/sits_cube.R                                                                           |  113 
 sits-1.5.0/sits/R/sits_cube_copy.R                                                                      |   24 
 sits-1.5.0/sits/R/sits_factory.R                                                                        |    2 
 sits-1.5.0/sits/R/sits_filters.R                                                                        |    9 
 sits-1.5.0/sits/R/sits_geo_dist.R                                                                       |    5 
 sits-1.5.0/sits/R/sits_get_data.R                                                                       |   62 
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 sits-1.5.0/sits/R/sits_label_classification.R                                                           |   78 
 sits-1.5.0/sits/R/sits_labels.R                                                                         |   81 
 sits-1.5.0/sits/R/sits_lighttae.R                                                                       |   57 
 sits-1.5.0/sits/R/sits_machine_learning.R                                                               |   71 
 sits-1.5.0/sits/R/sits_merge.R                                                                          |  162 -
 sits-1.5.0/sits/R/sits_mixture_model.R                                                                  |   34 
 sits-1.5.0/sits/R/sits_mlp.R                                                                            |   70 
 sits-1.5.0/sits/R/sits_mosaic.R                                                                         |    5 
 sits-1.5.0/sits/R/sits_patterns.R                                                                       |    7 
 sits-1.5.0/sits/R/sits_plot.R                                                                           |  556 ++-
 sits-1.5.0/sits/R/sits_predictors.R                                                                     |    8 
 sits-1.5.0/sits/R/sits_reclassify.R                                                                     |   45 
 sits-1.5.0/sits/R/sits_reduce.R                                                                         |only
 sits-1.5.0/sits/R/sits_regularize.R                                                                     |  139 
 sits-1.5.0/sits/R/sits_resnet.R                                                                         |   87 
 sits-1.5.0/sits/R/sits_sample_functions.R                                                               |  277 +
 sits-1.5.0/sits/R/sits_segmentation.R                                                                   |   45 
 sits-1.5.0/sits/R/sits_select.R                                                                         |   65 
 sits-1.5.0/sits/R/sits_sf.R                                                                             |    1 
 sits-1.5.0/sits/R/sits_smooth.R                                                                         |  102 
 sits-1.5.0/sits/R/sits_som.R                                                                            |  116 
 sits-1.5.0/sits/R/sits_summary.R                                                                        |   29 
 sits-1.5.0/sits/R/sits_tae.R                                                                            |   54 
 sits-1.5.0/sits/R/sits_tempcnn.R                                                                        |   93 
 sits-1.5.0/sits/R/sits_timeline.R                                                                       |   32 
 sits-1.5.0/sits/R/sits_train.R                                                                          |   15 
 sits-1.5.0/sits/R/sits_tuning.R                                                                         |   30 
 sits-1.5.0/sits/R/sits_uncertainty.R                                                                    |   91 
 sits-1.5.0/sits/R/sits_utils.R                                                                          |    2 
 sits-1.5.0/sits/R/sits_validate.R                                                                       |   33 
 sits-1.5.0/sits/R/sits_variance.R                                                                       |   57 
 sits-1.5.0/sits/R/sits_view.R                                                                           |  204 -
 sits-1.5.0/sits/R/sits_xlsx.R                                                                           |   66 
 sits-1.5.0/sits/R/zzz.R                                                                                 |    4 
 sits-1.5.0/sits/demo/classify_cbers_bdc.R                                                               |   11 
 sits-1.5.0/sits/demo/classify_deeplearning.R                                                            |    8 
 sits-1.5.0/sits/demo/classify_raster_rfor.R                                                             |   12 
 sits-1.5.0/sits/demo/classify_ts.R                                                                      |    4 
 sits-1.5.0/sits/demo/dl_comparison.R                                                                    |   26 
 sits-1.5.0/sits/demo/evaluate_samples_Kohonen.R                                                         |    9 
 sits-1.5.0/sits/demo/ml_comparison.R                                                                    |   26 
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 sits-1.5.0/sits/inst/extdata/config_colors.yml                                                          |   33 
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 sits-1.5.0/sits/man/plot.class_cube.Rd                                                                  |   16 
 sits-1.5.0/sits/man/plot.class_vector_cube.Rd                                                           |   12 
 sits-1.5.0/sits/man/plot.probs_cube.Rd                                                                  |   22 
 sits-1.5.0/sits/man/plot.probs_vector_cube.Rd                                                           |   19 
 sits-1.5.0/sits/man/plot.raster_cube.Rd                                                                 |   21 
 sits-1.5.0/sits/man/plot.uncertainty_cube.Rd                                                            |   20 
 sits-1.5.0/sits/man/plot.uncertainty_vector_cube.Rd                                                     |only
 sits-1.5.0/sits/man/plot.variance_cube.Rd                                                               |   20 
 sits-1.5.0/sits/man/plot.vector_cube.Rd                                                                 |   22 
 sits-1.5.0/sits/man/plot.xgb_model.Rd                                                                   |   13 
 sits-1.5.0/sits/man/sits-package.Rd                                                                     |    1 
 sits-1.5.0/sits/man/sits_apply.Rd                                                                       |   12 
 sits-1.5.0/sits/man/sits_bands.Rd                                                                       |    3 
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 sits-1.5.0/sits/man/sits_cluster_dendro.Rd                                                              |    3 
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 sits-1.5.0/sits/man/sits_colors_set.Rd                                                                  |   51 
 sits-1.5.0/sits/man/sits_colors_show.Rd                                                                 |    2 
 sits-1.5.0/sits/man/sits_cube.Rd                                                                        |   56 
 sits-1.5.0/sits/man/sits_cube_copy.Rd                                                                   |    6 
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 sits-1.5.0/sits/man/sits_to_xlsx.Rd                                                                     |   13 
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 sits-1.5.0/sits/man/sits_variance.Rd                                                                    |   11 
 sits-1.5.0/sits/man/sits_view.Rd                                                                        |   27 
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 sits-1.5.0/sits/tests/testthat/test-cube_copy.R                                                         |    5 
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 sits-1.5.0/sits/tests/testthat/test-mosaic.R                                                            |    6 
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 sits-1.5.0/sits/tests/testthat/test-roi.R                                                               |    2 
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 sits-1.5.0/sits/tests/testthat/test-segmentation.R                                                      |  187 +
 sits-1.5.0/sits/tests/testthat/test-sf.R                                                                |    3 
 sits-1.5.0/sits/tests/testthat/test-som.R                                                               |   22 
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Package PopGenHelpR updated to version 1.3.0 with previous version 1.2.1 dated 2023-08-16

Title: Streamline Population Genomic and Genetic Analyses
Description: Estimate commonly used population genomic statistics and generate publication quality figures. 'PopGenHelpR' uses vcf, 'geno' (012), and csv files to generate output.
Author: Keaka Farleigh [aut, cph, cre] , Mason Murphy [aut, cph, ctb] , Christopher Blair [aut, cph, ctb] , Tereza Jezkova [aut, cph, ctb]
Maintainer: Keaka Farleigh <keakafarleigh@gmail.com>

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Package arcgisutils updated to version 0.3.0 with previous version 0.2.0 dated 2024-02-22

Title: ArcGIS Utility Functions
Description: Developer oriented utility functions designed to be used as the building blocks of R packages that work with ArcGIS Location Services. It provides functionality for authorization, Esri JSON construction and parsing, as well as other utilities pertaining to geometry and Esri type conversions. To support 'ArcGIS Pro' users, authorization can be done via 'arcgisbinding'. Installation instructions for 'arcgisbinding' can be found at <https://r.esri.com/r-bridge-site/arcgisbinding/installing-arcgisbinding.html>.
Author: Josiah Parry [aut, cre] , Kenneth Vernon [ctb] , Martha Bass [ctb]
Maintainer: Josiah Parry <josiah.parry@gmail.com>

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Package dowser updated to version 2.2.0 with previous version 2.1.0 dated 2023-12-22

Title: B Cell Receptor Phylogenetics Toolkit
Description: Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. Provides methods to 1) reconstruct unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple methods, 3) visualize trees with metadata at the tips, 4) reconstruct intermediate sequences, 5) detect biased ancestor-descendant relationships among metadata types Workflow examples available at documentation site (see URL). Citations: Hoehn et al (2022) <doi:10.1371/journal.pcbi.1009885>, Hoehn et al (2021) <doi:10.1101/2021.01.06.425648>.
Author: Kenneth Hoehn [aut, cre], Cole Jensen [ctb], Susanna Marquez [ctb], Jason Vander Heiden [ctb], Steven Kleinstein [aut, cph]
Maintainer: Kenneth Hoehn <kenneth.b.hoehn@dartmouth.edu>

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Package CleanBSequences updated to version 2.3.0 with previous version 1.4.0 dated 2022-04-28

Title: Curing of Biological Sequences
Description: Curates biological sequences massively, quickly, without errors and without internet connection. Biological sequences curing is performed by aligning the forward and / or revers primers or ends of cloning vectors with the sequences to be cleaned. After the alignment, new subsequences are generated without biological fragment not desired by the user. Pozzi et al (2020) <doi:10.1007/s00438-020-01671-z>.
Author: Florencia I. Pozzi, Silvina A. Felitti
Maintainer: Florencia I. Pozzi <florenciapoz@hotmail.com>

Diff between CleanBSequences versions 1.4.0 dated 2022-04-28 and 2.3.0 dated 2024-05-09

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Package backbone updated to version 2.1.4 with previous version 2.1.3 dated 2024-01-24

Title: Extracts the Backbone from Graphs
Description: An implementation of methods for extracting an unweighted unipartite graph (i.e. a backbone) from an unweighted unipartite graph, a weighted unipartite graph, the projection of an unweighted bipartite graph, or the projection of a weighted bipartite graph (Neal, 2022 <doi:10.1371/journal.pone.0269137>).
Author: Zachary Neal [aut, cre] , Rachel Domagalski [ctb], Bruce Sagan [ctb], Karl Godard [ctb]
Maintainer: Zachary Neal <zpneal@msu.edu>

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Package mirai.promises (with last version 0.5.0) was removed from CRAN

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

2024-04-13 0.5.0
2023-12-05 0.4.1
2023-11-05 0.4.0
2023-09-25 0.3.1
2023-09-02 0.3.0
2023-08-25 0.2.0
2023-08-09 0.1.2
2023-06-19 0.1.1
2023-05-31 0.1.0

Permanent link
Package neurobase updated to version 1.32.4 with previous version 1.32.3 dated 2022-10-23

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 logr updated to version 1.3.8 with previous version 1.3.7 dated 2024-04-07

Title: Creates Log Files
Description: Contains functions to help create log files. The package aims to overcome the difficulty of the base R sink() command. The log_print() function will print to both the console and the file log, without interfering in other write operations.
Author: David Bosak [aut, cre], Rikard Isaksson [ctb]
Maintainer: David Bosak <dbosak01@gmail.com>

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Package insurancerating updated to version 0.7.3 with previous version 0.7.2 dated 2022-12-20

Title: Analytic Insurance Rating Techniques
Description: Methods for insurance rating. It helps actuaries to implement GLMs within all relevant steps needed to construct a risk premium from raw data. It provides a data driven strategy for the construction of insurance tariff classes. This strategy is based on the work by Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>. It also provides recipes on how to easily perform one-way, or univariate, analyses on an insurance portfolio. In addition it adds functionality to include reference categories in the levels of the coefficients in the output of a generalized linear regression analysis.
Author: Martin Haringa [aut, cre]
Maintainer: Martin Haringa <mtharinga@gmail.com>

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Package tiledb updated to version 0.27.0 with previous version 0.26.0 dated 2024-04-15

Title: Modern Database Engine for Complex Data Based on Multi-Dimensional Arrays
Description: The modern database 'TileDB' introduces a powerful on-disk format for storing and accessing any complex data based on multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations. This package provides the R support.
Author: TileDB, Inc. [aut, cph], Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>

Diff between tiledb versions 0.26.0 dated 2024-04-15 and 0.27.0 dated 2024-05-09

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Package splines2 updated to version 0.5.2 with previous version 0.5.1 dated 2023-08-19

Title: Regression Spline Functions and Classes
Description: Constructs basis functions of B-splines, M-splines, I-splines, convex splines (C-splines), periodic splines, natural cubic splines, generalized Bernstein polynomials, their derivatives, and integrals (except C-splines) by closed-form recursive formulas. It also contains a C++ head-only library integrated with Rcpp. See Wang and Yan (2021) <doi:10.6339/21-JDS1020> for details.
Author: Wenjie Wang [aut, cre] , Jun Yan [aut]
Maintainer: Wenjie Wang <wang@wwenjie.org>

Diff between splines2 versions 0.5.1 dated 2023-08-19 and 0.5.2 dated 2024-05-09

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New package ptm with initial version 0.2.7
Package: ptm
Title: Analyses of Protein Post-Translational Modifications
Version: 0.2.7
Description: Contains utilities for the analysis of post-translational modifications (PTMs) in proteins, with particular emphasis on the sulfoxidation of methionine residues. Features include the ability to download, filter and analyze data from the sulfoxidation database 'MetOSite', and integrate data from other main PTMs (other databases). Utilities to search and characterize S-aromatic motifs in proteins are also provided. In addition, functions to analyze sequence environments around modifiable residues in proteins can be found. For instance, 'ptm' allows to search for amino acids either overrepresented or avoided around the modifiable residues from the proteins of interest. Functions tailored to test statistical hypothesis related to these differential sequence environments are also implemented. A number of utilities to assess the effect of the modification/mutation of a given residue on the protein stability, have also been included in this package. Further and detailed information regarding [...truncated...]
License: GPL (>= 2)
URL: https://bitbucket.org/jcaledo/ptm, https://metositeptm.com
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: bio3d (>= 2.3-4), curl, graphics, httr (>= 1.3.1), igraph, jsonlite, RCurl, seqinr, stats, utils, xml2
Suggests: Biostrings, KEGGREST, knitr, markdown, muscle, testthat
NeedsCompilation: no
Packaged: 2024-05-07 06:47:31 UTC; JCA
Author: Juan Carlos Aledo [aut, cre]
Maintainer: Juan Carlos Aledo <caledo@uma.es>
Repository: CRAN
Date/Publication: 2024-05-09 14:30:02 UTC

More information about ptm at CRAN
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Package leaflegend updated to version 1.2.1 with previous version 1.2.0 dated 2024-01-10

Title: Add Custom Legends to 'leaflet' Maps
Description: Provides extensions to the 'leaflet' package to customize legends with images, text styling, orientation, sizing, and symbology and functions to create symbols to plot on maps.
Author: Thomas Roh [aut, cre], Ricardo Rodrigo Basa [ctb]
Maintainer: Thomas Roh <thomas@roh.engineering>

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Package ctsem updated to version 3.10.0 with previous version 3.9.1 dated 2023-10-30

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous (and discrete) time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models. Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. Nonlinearities, (state dependent parameters) and random effects on all parameters are possible, using either max likelihood / max a posteriori optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Mod [...truncated...]
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <charles.driver2@uzh.ch>

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Package tclust updated to version 2.0-4 with previous version 2.0-3 dated 2024-04-17

Title: Robust Trimmed Clustering
Description: Provides functions for robust trimmed clustering. The methods are described in Garcia-Escudero (2008) <doi:10.1214/07-AOS515>, Fritz et al. (2012) <doi:10.18637/jss.v047.i12>, Garcia-Escudero et al. (2011) <doi:10.1007/s11222-010-9194-z> and others.
Author: Valentin Todorov [aut, cre] , Luis Angel Garcia Escudero [aut], Agustin Mayo Iscar [aut], Javier Crespo Guerrero [aut], Heinrich Fritz [aut]
Maintainer: Valentin Todorov <valentin.todorov@chello.at>

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Package regional updated to version 0.4.4 with previous version 0.3.3 dated 2022-03-14

Title: Intra- and Inter-Regional Similarity
Description: Calculates intra-regional and inter-regional similarities based on user-provided spatial vector objects (regions) and spatial raster objects (cells with values). Implemented metrics include inhomogeneity, isolation (Haralick and Shapiro (1985) <doi:10.1016/S0734-189X(85)90153-7>, Jasiewicz et al. (2018) <doi:10.1016/j.cageo.2018.06.003>), and distinction (Nowosad (2021) <doi:10.1080/13658816.2021.1893324>).
Author: Jakub Nowosad [aut, cre]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package MIMER updated to version 1.0.1 with previous version 1.0.0 dated 2024-05-08

Title: Data Wrangling for Antimicrobial Resistance Studies
Description: Designed for analyzing the Medical Information Mart for Intensive Care(MIMIC) dataset, a repository of freely accessible electronic health records. MIMER(MIMIC-enabled Research) package, offers a suite of data wrangling functions tailored specifically for preparing the dataset for research purposes, particularly in antimicrobial resistance(AMR) studies. It simplifies complex data manipulation tasks, allowing researchers to focus on their primary inquiries without being bogged down by wrangling complexities.
Author: Anoop Velluva [aut, cre] , Alessandro Gerada [ctb] , Alexander Howard [ctb]
Maintainer: Anoop Velluva <anoop.velluva@liverpool.ac.uk>

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Package lessR updated to version 4.3.3 with previous version 4.3.2 dated 2024-04-07

Title: Less Code, More Results
Description: Each function accomplishes the work of multiple standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for comprehensive summary statistics via pivot tables, a comprehensive regression analysis, ANOVA and t-test, visualizations including the Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, and Trellis graphics. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, generation and rendering of regression instructions for interpretative output, and interactive visualizations.
Author: David Gerbing, The School of Business, Portland State University
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package evreg updated to version 1.1.1 with previous version 1.1.0 dated 2024-05-08

Title: Evidential Regression
Description: An implementation of the 'Evidential Neural Network for Regression' model recently introduced in Denoeux (2023) <doi:10.1109/TFUZZ.2023.3268200>. In this model, prediction uncertainty is quantified by Gaussian random fuzzy numbers as introduced in Denoeux (2023) <doi:10.1016/j.fss.2022.06.004>. The package contains functions for training the network, tuning hyperparameters by cross-validation or the hold-out method, and making predictions. It also contains utilities for making calculations with Gaussian random fuzzy numbers (such as, e.g., computing the degrees of belief and plausibility of an interval, or combining Gaussian random fuzzy numbers).
Author: Thierry Denoeux [aut, cre]
Maintainer: Thierry Denoeux <tdenoeux@utc.fr>

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Package CoImp updated to version 2.0.0 with previous version 1.0 dated 2019-06-28

Title: Parametric and Non-Parametric Copula-Based Imputation Methods
Description: Copula-based imputation methods: parametric and non-parametric algorithms for missing multivariate data through conditional copulas.
Author: Francesca Marta Lilja Di Lascio [aut, cre], Aurora Gatto [aut], Simone Giannerini [aut]
Maintainer: Francesca Marta Lilja Di Lascio <marta.dilascio@unibz.it>

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 man/MCAR-class.Rd        |    4 +---
 man/MCAR.Rd              |    4 +---
 man/NPCoImp-class.Rd     |only
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 man/PerfMeasure-class.Rd |    9 ++++-----
 man/PerfMeasure.Rd       |    4 +---
 21 files changed, 71 insertions(+), 73 deletions(-)

More information about CoImp at CRAN
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Package traveltimeR updated to version 1.2.1 with previous version 1.2.0 dated 2024-04-11

Title: Interface to 'Travel Time' API
Description: 'Travel Time' API <https://docs.traveltime.com/api/overview/introduction> helps users find locations by journey time rather than using ‘as the crow flies’ distance. Time-based searching gives users more opportunities for personalisation and delivers a more relevant search.
Author: TravelTime [aut, cre]
Maintainer: TravelTime <frontend@traveltime.com>

Diff between traveltimeR versions 1.2.0 dated 2024-04-11 and 1.2.1 dated 2024-05-09

 DESCRIPTION       |    6 +++---
 MD5               |    4 ++--
 R/make_searches.R |   15 ++++++++++-----
 3 files changed, 15 insertions(+), 10 deletions(-)

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Package qicharts2 updated to version 0.7.5 with previous version 0.7.4 dated 2023-08-21

Title: Quality Improvement Charts
Description: Functions for making run charts, Shewhart control charts and Pareto charts for continuous quality improvement. Included control charts are: I, MR, Xbar, S, T, C, U, U', P, P', and G charts. Non-random variation in the form of minor to moderate persistent shifts in data over time is identified by the Anhoej rules for unusually long runs and unusually few crossing [Anhoej, Olesen (2014) <doi:10.1371/journal.pone.0113825>]. Non-random variation in the form of larger, possibly transient, shifts is identified by Shewhart's 3-sigma rule [Mohammed, Worthington, Woodall (2008) <doi:10.1136/qshc.2004.012047>].
Author: Jacob Anhoej [aut, cre]
Maintainer: Jacob Anhoej <jacob@anhoej.net>

Diff between qicharts2 versions 0.7.4 dated 2023-08-21 and 0.7.5 dated 2024-05-09

 qicharts2-0.7.4/qicharts2/NEWS                    |only
 qicharts2-0.7.5/qicharts2/DESCRIPTION             |   10 ++++----
 qicharts2-0.7.5/qicharts2/MD5                     |   26 +++++++++++-----------
 qicharts2-0.7.5/qicharts2/NEWS.md                 |only
 qicharts2-0.7.5/qicharts2/R/bchart.R              |   14 +++++------
 qicharts2-0.7.5/qicharts2/R/data.R                |    2 -
 qicharts2-0.7.5/qicharts2/R/qic.plot.R            |    7 -----
 qicharts2-0.7.5/qicharts2/README.md               |    4 ++-
 qicharts2-0.7.5/qicharts2/build/partial.rdb       |binary
 qicharts2-0.7.5/qicharts2/build/vignette.rds      |binary
 qicharts2-0.7.5/qicharts2/inst/doc/qicharts2.R    |   22 +++++++++---------
 qicharts2-0.7.5/qicharts2/inst/doc/qicharts2.Rmd  |    2 -
 qicharts2-0.7.5/qicharts2/inst/doc/qicharts2.html |   10 ++++----
 qicharts2-0.7.5/qicharts2/man/gtt.Rd              |    2 -
 qicharts2-0.7.5/qicharts2/vignettes/qicharts2.Rmd |    2 -
 15 files changed, 49 insertions(+), 52 deletions(-)

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