Thu, 05 Sep 2024

Package SmallCountRounding updated to version 1.0.5 with previous version 1.0.3 dated 2022-11-16

Title: Small Count Rounding of Tabular Data
Description: A statistical disclosure control tool to protect frequency tables in cases where small values are sensitive. The function PLSrounding() performs small count rounding of necessary inner cells so that all small frequencies of cross-classifications to be published (publishable cells) are rounded. This is equivalent to changing micro data since frequencies of unique combinations are changed. Thus, additivity and consistency are guaranteed. The methodology is described in Langsrud and Heldal (2018) <https://www.researchgate.net/publication/327768398_An_Algorithm_for_Small_Count_Rounding_of_Tabular_Data>.
Author: Oeyvind Langsrud [aut, cre], Johan Heldal [aut]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

Diff between SmallCountRounding versions 1.0.3 dated 2022-11-16 and 1.0.5 dated 2024-09-05

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Permanent link

Package HYPEtools updated to version 1.6.3 with previous version 1.6.2 dated 2024-05-23

Title: Tools for Processing and Analyzing Files from the Hydrological Catchment Model HYPE
Description: Work with model files (setup, input, output) from the hydrological catchment model HYPE: Streamlined file import and export, standard evaluation plot routines, diverse post-processing and aggregation routines for hydrological model analysis. The HYPEtools package is also archived at <doi:10.5281/zenodo.7627955> and can be cited in publications with Brendel et al. (2024) <doi:10.1016/j.envsoft.2024.106094>.
Author: Rene Capell [aut, cre] , Conrad Brendel [aut] , Jafet Andersson [ctb], David Gustafsson [ctb], Jude Musuuza [ctb], Jude Lubega [ctb]
Maintainer: Rene Capell <hypetools.rene@smhi.se>

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More information about HYPEtools at CRAN
Permanent link

Package httk updated to version 2.4.0 with previous version 2.3.1 dated 2024-03-26

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] , Nathan Pollesch [ctb] , Miyuki Breen [ctb] , Shannon Bell [ctb] , Xia [...truncated...]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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More information about httk at CRAN
Permanent link

Package gtsummary updated to version 2.0.2 with previous version 2.0.1 dated 2024-08-17

Title: Presentation-Ready Data Summary and Analytic Result Tables
Description: Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.
Author: Daniel D. Sjoberg [aut, cre] , Joseph Larmarange [aut] , Michael Curry [aut] , Jessica Lavery [aut] , Karissa Whiting [aut] , Emily C. Zabor [aut] , Xing Bai [ctb], Esther Drill [ctb] , Jessica Flynn [ctb] , Margie Hannum [ctb] , Stephanie Lobaugh [c [...truncated...]
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

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Package segmented updated to version 2.1-2 with previous version 2.1-1 dated 2024-07-26

Title: Regression Models with Break-Points / Change-Points Estimation (with Possibly Random Effects)
Description: Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects. Multiple breakpoints for the same variable are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, <doi:10.1177/1471082X13504721>). Estimation of piecewise-constant relationships and changepoints (mean-shift models) is discussed in Fasola et al. (2018, <doi:10.1007/s00180-017-0740-4>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

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Package datamods updated to version 1.5.2 with previous version 1.5.1 dated 2024-05-16

Title: Modules to Import and Manipulate Data in 'Shiny'
Description: 'Shiny' modules to import data into an application or 'addin' from various sources, and to manipulate them after that.
Author: Victor Perrier [aut, cre, cph], Fanny Meyer [aut], Samra Goumri [aut], Zauad Shahreer Abeer [aut], Eduard Szoecs [ctb]
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Package tabula updated to version 3.1.1 with previous version 3.1.0 dated 2024-05-16

Title: Analysis and Visualization of Archaeological Count Data
Description: An easy way to examine archaeological count data. This package provides several tests and measures of diversity: heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.), richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and similarity (Brainerd-Robinson, etc.). It allows to easily visualize count data and statistical thresholds: rank vs abundance plots, heatmaps, Ford (1962) and Bertin (1977) diagrams, etc.
Author: Nicolas Frerebeau [aut, cre] , Brice Lebrun [ctb] , Matthew Peeples [ctb] , Ben Marwick [ctb] , Anne Philippe [ctb] , Jean-Baptiste Fourvel [ctb] , Universite Bordeaux Montaigne [fnd], CNRS [fnd]
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>

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Package liver updated to version 1.16 with previous version 1.15 dated 2023-11-01

Title: "Eating the Liver of Data Science"
Description: Offers a suite of helper functions to simplify various data science techniques for non-experts. This package aims to enable individuals with only a minimal level of coding knowledge to become acquainted with these techniques in an accessible manner. Inspired by an ancient Persian idiom, we liken this process to "eating the liver of data science," suggesting a deep and intimate engagement with the field of data science. This package includes functions for tasks such as data partitioning for out-of-sample testing, calculating Mean Squared Error (MSE) to assess prediction accuracy, and data transformations (z-score and min-max). In addition to these helper functions, the 'liver' package also features several intriguing datasets valuable for multivariate analysis.
Author: Reza Mohammadi [aut, cre] , Kevin Burke [aut]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

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Package keras3 updated to version 1.2.0 with previous version 1.1.0 dated 2024-07-17

Title: R Interface to 'Keras'
Description: Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.
Author: Tomasz Kalinowski [aut, cph, cre], Daniel Falbel [ctb, cph], JJ Allaire [aut, cph], Francois Chollet [aut, cph], Posit Software, PBC [cph, fnd], Google [cph, fnd], Yuan Tang [ctb, cph] , Wouter Van Der Bijl [ctb, cph], Martin Studer [ctb, cph], Sigri [...truncated...]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

Diff between keras3 versions 1.1.0 dated 2024-07-17 and 1.2.0 dated 2024-09-05

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 inst/doc/functional_api.Rmd                                |   16 
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 inst/doc/intro_to_keras_for_engineers.Rmd                  |   29 
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 inst/doc/making_new_layers_and_models_via_subclassing.Rmd  |    6 
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 inst/doc/transfer_learning.Rmd                             |   10 
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 man/Layer.Rd                                               |   10 
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 man/callback_backup_and_restore.Rd                         |    4 
 man/image_dataset_from_directory.Rd                        |   13 
 man/image_smart_resize.Rd                                  |    6 
 man/keras_input.Rd                                         |    3 
 man/layer_conv_2d.Rd                                       |    8 
 man/layer_conv_3d.Rd                                       |    8 
 man/layer_dense.Rd                                         |    4 
 man/layer_einsum_dense.Rd                                  |    2 
 man/layer_embedding.Rd                                     |    4 
 man/layer_feature_space.Rd                                 |    6 
 man/layer_input.Rd                                         |    3 
 man/layer_string_lookup.Rd                                 |    4 
 man/layer_tfsm.Rd                                          |    4 
 man/layer_zero_padding_1d.Rd                               |   32 
 man/loss_binary_crossentropy.Rd                            |    3 
 man/loss_binary_focal_crossentropy.Rd                      |    3 
 man/loss_categorical_crossentropy.Rd                       |    3 
 man/loss_categorical_focal_crossentropy.Rd                 |    3 
 man/loss_categorical_hinge.Rd                              |    3 
 man/loss_cosine_similarity.Rd                              |    3 
 man/loss_ctc.Rd                                            |    3 
 man/loss_dice.Rd                                           |    3 
 man/loss_hinge.Rd                                          |    3 
 man/loss_huber.Rd                                          |    3 
 man/loss_kl_divergence.Rd                                  |    5 
 man/loss_log_cosh.Rd                                       |    3 
 man/loss_mean_absolute_error.Rd                            |    3 
 man/loss_mean_absolute_percentage_error.Rd                 |    3 
 man/loss_mean_squared_error.Rd                             |    3 
 man/loss_mean_squared_logarithmic_error.Rd                 |    3 
 man/loss_poisson.Rd                                        |    5 
 man/loss_sparse_categorical_crossentropy.Rd                |    3 
 man/loss_squared_hinge.Rd                                  |    3 
 man/loss_tversky.Rd                                        |    3 
 man/metric_binary_iou.Rd                                   |   20 
 man/metric_categorical_crossentropy.Rd                     |    1 
 man/metric_iou.Rd                                          |   20 
 man/metric_mean_iou.Rd                                     |   20 
 man/metric_one_hot_iou.Rd                                  |   26 
 man/metric_one_hot_mean_iou.Rd                             |   11 
 man/op_abs.Rd                                              |    2 
 man/op_add.Rd                                              |    2 
 man/op_all.Rd                                              |    2 
 man/op_any.Rd                                              |    2 
 man/op_append.Rd                                           |    2 
 man/op_arange.Rd                                           |    2 
 man/op_arccos.Rd                                           |    2 
 man/op_arccosh.Rd                                          |    2 
 man/op_arcsin.Rd                                           |    2 
 man/op_arcsinh.Rd                                          |    2 
 man/op_arctan.Rd                                           |    2 
 man/op_arctan2.Rd                                          |    2 
 man/op_arctanh.Rd                                          |    2 
 man/op_argmax.Rd                                           |    2 
 man/op_argmin.Rd                                           |    2 
 man/op_argpartition.Rd                                     |    2 
 man/op_argsort.Rd                                          |    2 
 man/op_array.Rd                                            |    2 
 man/op_associative_scan.Rd                                 |only
 man/op_average.Rd                                          |    2 
 man/op_average_pool.Rd                                     |    2 
 man/op_batch_normalization.Rd                              |    2 
 man/op_binary_crossentropy.Rd                              |    2 
 man/op_bincount.Rd                                         |    2 
 man/op_broadcast_to.Rd                                     |    2 
 man/op_cast.Rd                                             |    4 
 man/op_categorical_crossentropy.Rd                         |    2 
 man/op_ceil.Rd                                             |    2 
 man/op_cholesky.Rd                                         |    2 
 man/op_clip.Rd                                             |    2 
 man/op_concatenate.Rd                                      |    2 
 man/op_cond.Rd                                             |    4 
 man/op_conj.Rd                                             |    2 
 man/op_conv.Rd                                             |    2 
 man/op_conv_transpose.Rd                                   |    2 
 man/op_convert_to_numpy.Rd                                 |    4 
 man/op_convert_to_tensor.Rd                                |    4 
 man/op_copy.Rd                                             |    2 
 man/op_correlate.Rd                                        |    2 
 man/op_cos.Rd                                              |    2 
 man/op_cosh.Rd                                             |    2 
 man/op_count_nonzero.Rd                                    |    2 
 man/op_cross.Rd                                            |    2 
 man/op_ctc_decode.Rd                                       |    2 
 man/op_ctc_loss.Rd                                         |    2 
 man/op_cumprod.Rd                                          |    2 
 man/op_cumsum.Rd                                           |    2 
 man/op_custom_gradient.Rd                                  |    4 
 man/op_depthwise_conv.Rd                                   |    2 
 man/op_det.Rd                                              |    2 
 man/op_diag.Rd                                             |    2 
 man/op_diagonal.Rd                                         |    2 
 man/op_diff.Rd                                             |    2 
 man/op_digitize.Rd                                         |    2 
 man/op_divide.Rd                                           |    2 
 man/op_divide_no_nan.Rd                                    |    2 
 man/op_dot.Rd                                              |    2 
 man/op_dtype.Rd                                            |    4 
 man/op_eig.Rd                                              |    2 
 man/op_eigh.Rd                                             |    2 
 man/op_einsum.Rd                                           |    2 
 man/op_elu.Rd                                              |    2 
 man/op_empty.Rd                                            |    2 
 man/op_equal.Rd                                            |    2 
 man/op_erf.Rd                                              |    2 
 man/op_erfinv.Rd                                           |    2 
 man/op_exp.Rd                                              |    2 
 man/op_expand_dims.Rd                                      |    2 
 man/op_expm1.Rd                                            |    2 
 man/op_extract_sequences.Rd                                |    2 
 man/op_eye.Rd                                              |    2 
 man/op_fft.Rd                                              |    2 
 man/op_fft2.Rd                                             |    2 
 man/op_flip.Rd                                             |    2 
 man/op_floor.Rd                                            |    2 
 man/op_floor_divide.Rd                                     |    2 
 man/op_fori_loop.Rd                                        |    4 
 man/op_full.Rd                                             |    2 
 man/op_full_like.Rd                                        |    2 
 man/op_gelu.Rd                                             |    2 
 man/op_get_item.Rd                                         |    2 
 man/op_greater.Rd                                          |    2 
 man/op_greater_equal.Rd                                    |    2 
 man/op_hard_sigmoid.Rd                                     |    2 
 man/op_hard_silu.Rd                                        |    2 
 man/op_hstack.Rd                                           |    2 
 man/op_identity.Rd                                         |    2 
 man/op_imag.Rd                                             |    2 
 man/op_image_affine_transform.Rd                           |    2 
 man/op_image_crop.Rd                                       |    2 
 man/op_image_extract_patches.Rd                            |    2 
 man/op_image_hsv_to_rgb.Rd                                 |    2 
 man/op_image_map_coordinates.Rd                            |    2 
 man/op_image_pad.Rd                                        |    2 
 man/op_image_resize.Rd                                     |    2 
 man/op_image_rgb_to_grayscale.Rd                           |    2 
 man/op_image_rgb_to_hsv.Rd                                 |    2 
 man/op_in_top_k.Rd                                         |    2 
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 man/op_irfft.Rd                                            |    2 
 man/op_is_tensor.Rd                                        |    4 
 man/op_isclose.Rd                                          |    2 
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 man/op_logical_or.Rd                                       |    2 
 man/op_logical_xor.Rd                                      |    2 
 man/op_logspace.Rd                                         |    2 
 man/op_logsumexp.Rd                                        |    6 
 man/op_lstsq.Rd                                            |    2 
 man/op_lu_factor.Rd                                        |    2 
 man/op_map.Rd                                              |    4 
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 man/op_mean.Rd                                             |    2 
 man/op_median.Rd                                           |    2 
 man/op_meshgrid.Rd                                         |    2 
 man/op_min.Rd                                              |    2 
 man/op_minimum.Rd                                          |    2 
 man/op_mod.Rd                                              |    2 
 man/op_moments.Rd                                          |    2 
 man/op_moveaxis.Rd                                         |    2 
 man/op_multi_hot.Rd                                        |    2 
 man/op_multiply.Rd                                         |    2 
 man/op_nan_to_num.Rd                                       |    2 
 man/op_ndim.Rd                                             |    2 
 man/op_negative.Rd                                         |    2 
 man/op_nonzero.Rd                                          |    2 
 man/op_norm.Rd                                             |    2 
 man/op_normalize.Rd                                        |    2 
 man/op_not_equal.Rd                                        |    2 
 man/op_one_hot.Rd                                          |    6 
 man/op_ones.Rd                                             |    2 
 man/op_ones_like.Rd                                        |    2 
 man/op_outer.Rd                                            |    2 
 man/op_pad.Rd                                              |    4 
 man/op_power.Rd                                            |    2 
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 man/op_psnr.Rd                                             |    4 
 man/op_qr.Rd                                               |    2 
 man/op_quantile.Rd                                         |    2 
 man/op_ravel.Rd                                            |    2 
 man/op_real.Rd                                             |    2 
 man/op_reciprocal.Rd                                       |    2 
 man/op_relu.Rd                                             |    2 
 man/op_relu6.Rd                                            |    2 
 man/op_repeat.Rd                                           |    2 
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 man/op_rfft.Rd                                             |    2 
 man/op_roll.Rd                                             |    2 
 man/op_round.Rd                                            |    2 
 man/op_rsqrt.Rd                                            |    2 
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 man/op_scatter.Rd                                          |    4 
 man/op_scatter_update.Rd                                   |    4 
 man/op_searchsorted.Rd                                     |only
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 man/op_shape.Rd                                            |    4 
 man/op_sigmoid.Rd                                          |    2 
 man/op_sign.Rd                                             |    2 
 man/op_silu.Rd                                             |    2 
 man/op_sin.Rd                                              |    2 
 man/op_sinh.Rd                                             |    2 
 man/op_size.Rd                                             |    2 
 man/op_slice.Rd                                            |    4 
 man/op_slice_update.Rd                                     |    4 
 man/op_slogdet.Rd                                          |    2 
 man/op_softmax.Rd                                          |    2 
 man/op_softplus.Rd                                         |    2 
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 man/op_solve.Rd                                            |    2 
 man/op_solve_triangular.Rd                                 |    2 
 man/op_sort.Rd                                             |    2 
 man/op_sparse_categorical_crossentropy.Rd                  |    4 
 man/op_split.Rd                                            |    2 
 man/op_sqrt.Rd                                             |    2 
 man/op_square.Rd                                           |    2 
 man/op_squeeze.Rd                                          |    2 
 man/op_stack.Rd                                            |    2 
 man/op_std.Rd                                              |    2 
 man/op_stft.Rd                                             |    2 
 man/op_stop_gradient.Rd                                    |    4 
 man/op_subtract.Rd                                         |    2 
 man/op_sum.Rd                                              |    2 
 man/op_svd.Rd                                              |    2 
 man/op_swapaxes.Rd                                         |    2 
 man/op_switch.Rd                                           |    4 
 man/op_take.Rd                                             |    2 
 man/op_take_along_axis.Rd                                  |    2 
 man/op_tan.Rd                                              |    2 
 man/op_tanh.Rd                                             |    2 
 man/op_tensordot.Rd                                        |    2 
 man/op_tile.Rd                                             |    2 
 man/op_top_k.Rd                                            |    4 
 man/op_trace.Rd                                            |    2 
 man/op_transpose.Rd                                        |    2 
 man/op_tri.Rd                                              |    2 
 man/op_tril.Rd                                             |    2 
 man/op_triu.Rd                                             |    2 
 man/op_unstack.Rd                                          |    4 
 man/op_var.Rd                                              |    2 
 man/op_vdot.Rd                                             |    2 
 man/op_vectorize.Rd                                        |    2 
 man/op_vectorized_map.Rd                                   |    4 
 man/op_vstack.Rd                                           |    2 
 man/op_where.Rd                                            |    2 
 man/op_while_loop.Rd                                       |    4 
 man/op_zeros.Rd                                            |    2 
 man/op_zeros_like.Rd                                       |    2 
 man/optimizer_adadelta.Rd                                  |    8 
 man/optimizer_adafactor.Rd                                 |    8 
 man/optimizer_adagrad.Rd                                   |    8 
 man/optimizer_adam.Rd                                      |    8 
 man/optimizer_adam_w.Rd                                    |    8 
 man/optimizer_adamax.Rd                                    |    8 
 man/optimizer_ftrl.Rd                                      |    8 
 man/optimizer_lamb.Rd                                      |only
 man/optimizer_lion.Rd                                      |    8 
 man/optimizer_loss_scale.Rd                                |    8 
 man/optimizer_nadam.Rd                                     |    8 
 man/optimizer_rmsprop.Rd                                   |    8 
 man/optimizer_sgd.Rd                                       |    8 
 man/pad_sequences.Rd                                       |    2 
 man/quantize_weights.Rd                                    |    4 
 man/save_model.Rd                                          |    5 
 man/shape.Rd                                               |    4 
 man/text_dataset_from_directory.Rd                         |   10 
 vignettes/custom_train_step_in_tensorflow.Rmd              |   24 
 vignettes/distributed_training_with_tensorflow.Rmd         |   14 
 vignettes/distribution.Rmd                                 |   23 
 vignettes/functional_api.Rmd                               |   16 
 vignettes/getting_started.Rmd                              |    8 
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 vignettes/intro_to_keras_for_engineers.Rmd                 |   29 
 vignettes/making_new_layers_and_models_via_subclassing.Rmd |    6 
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 vignettes/transfer_learning.Rmd                            |   10 
 vignettes/understanding_masking_and_padding.Rmd            |    4 
 vignettes/writing_a_custom_training_loop_in_tensorflow.Rmd |    4 
 346 files changed, 1955 insertions(+), 897 deletions(-)

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Package FossilSim updated to version 2.4.0 with previous version 2.3.3 dated 2024-04-29

Title: Simulation and Plots for Fossil and Taxonomy Data
Description: Simulating and plotting taxonomy and fossil data on phylogenetic trees under mechanistic models of speciation, preservation and sampling.
Author: Rachel Warnock [aut, cph], Joelle Barido-Sottani [aut, cre, cph], Walker Pett [aut, cph], O'Reilly Joseph [aut, cph], UgnÄ— Stolz [aut, cph]
Maintainer: Joelle Barido-Sottani <joelle.barido-sottani@m4x.org>

Diff between FossilSim versions 2.3.3 dated 2024-04-29 and 2.4.0 dated 2024-09-05

 DESCRIPTION                        |   24 
 MD5                                |   53 
 NAMESPACE                          |   11 
 NEWS.md                            |  144 +-
 R/FossilSim.R                      |  102 -
 R/SAtree.R                         |    2 
 R/conversions.R                    |   22 
 R/fbdrange.R                       |only
 R/fossils.R                        |   14 
 R/plot.fbdrange.R                  |only
 R/sim.taxonomy.R                   |    1 
 R/sysdata.rda                      |only
 build/vignette.rds                 |binary
 inst/doc/SAtree.R                  |   42 
 inst/doc/SAtree.html               |  947 ++++++++---------
 inst/doc/fossils.R                 |  582 +++++-----
 inst/doc/fossils.html              | 1978 ++++++++++++++++++-------------------
 inst/doc/intro.R                   |   62 -
 inst/doc/intro.html                |  992 +++++++++---------
 inst/doc/paleotree.R               |   44 
 inst/doc/paleotree.html            | 1050 +++++++++++--------
 inst/doc/simfbd.R                  |   48 
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 inst/doc/taxonomy.R                |  112 +-
 inst/doc/taxonomy.html             | 1308 ++++++++++++------------
 inst/extdata                       |only
 man/FossilSim.Rd                   |    3 
 man/fbdrange.Rd                    |only
 man/get_fbdrange_from_file.Rd      |only
 man/paleotree.record.to.fossils.Rd |    4 
 man/plot.fbdrange.Rd               |only
 31 files changed, 4342 insertions(+), 4135 deletions(-)

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New package twoStageDesignTMLE with initial version 1.0
Package: twoStageDesignTMLE
Title: Targeted Maximum Likelihood Estimation for Two-Stage Study Design
Version: 1.0
Author: Susan Gruber [aut, cre], Mark van der Laan [aut]
Maintainer: Susan Gruber <sgruber@TLrevolution.com>
Copyright: Copyright 2024. TL Revolution LLC. All Rights Reserved.
Description: An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.
Depends: tmle (>= 2.0)
Suggests: dbarts (>= 0.9-18), glmnet
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-03 16:58:22 UTC; susan
Repository: CRAN
Date/Publication: 2024-09-05 17:20:02 UTC

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New package pcvr with initial version 1.0.0
Package: pcvr
Title: Plant Phenotyping and Bayesian Statistics
Version: 1.0.0
Maintainer: Josh Sumner <jsumner@danforthcenter.org>
Description: Analyse common types of plant phenotyping data, provide a simplified interface to longitudinal growth modeling and select Bayesian statistics, and streamline use of 'PlantCV' output. Several Bayesian methods and reporting guidelines for Bayesian methods are described in Kruschke (2018) <doi:10.1177/2515245918771304>, Kruschke (2013) <doi:10.1037/a0029146>, and Kruschke (2021) <doi:10.1038/s41562-021-01177-7>.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Additional_repositories: https://mc-stan.org/r-packages/
Imports: FactoMineR, rlang, stats, utils, methods, data.table, ggplot2, ggridges, igraph, jsonlite, lme4, patchwork, extraDistr, parallel, bayestestR, viridis, mgcv, quantreg, nlme, splines, lmeSplines, scales, survival, car
Suggests: knitr, rmarkdown, brms, flexsurv, curl, cmdstanr, rstan, caret, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/danforthcenter/pcvr, https://plantcv.org/, https://danforthcenter.github.io/pcvr/
BugReports: https://github.com/danforthcenter/pcvr/issues
NeedsCompilation: no
Packaged: 2024-09-03 19:54:03 UTC; josh
Author: Josh Sumner [aut, cre] , Jeffrey Berry [aut] , Noah Fahlgren [rev] , Donald Danforth Plant Science Center [cph]
Repository: CRAN
Date/Publication: 2024-09-05 17:30:02 UTC

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New package mmints with initial version 0.1.0
Package: mmints
Title: Workflows for Building Web Applications
Version: 0.1.0
Description: Sharing statistical methods or simulation frameworks through 'shiny' applications often requires workflows for handling data. To help save and display simulation results, the postgresUI() and postgresServer() functions in 'mmints' help with persistent data storage using a 'PostgreSQL' database. The 'mmints' package also offers data upload functionality through the csvUploadUI() and csvUploadServer() functions which allow users to upload data, view variables and their types, and edit variable types before fitting statistical models within the 'shiny' application. These tools aim to enhance efficiency and user interaction in 'shiny' based statistical and simulation applications.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/mightymetrika/mmints
BugReports: https://github.com/mightymetrika/mmints/issues
Suggests: testthat (>= 3.0.0)
Imports: DT, pool, RPostgres, shiny
NeedsCompilation: no
Packaged: 2024-09-03 20:55:11 UTC; Administrator
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-05 17:30:06 UTC

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New package hdar with initial version 1.0.0
Package: hdar
Title: 'REST' API Client for Accessing Data on 'WEkEO HDA V2'
Version: 1.0.0
URL: https://www.wekeo.eu/
BugReports: https://github.com/eea/hdar/issues
Maintainer: Matteo Mattiuzzi <matteo@mattiuzzi.com>
Description: Provides seamless access to the WEkEO Harmonised Data Access (HDA) API, enabling users to query, download, and process data efficiently from the HDA platform. With 'hdar', researchers and data scientists can integrate the extensive HDA datasets into their R workflows, enhancing their data analysis capabilities. Comprehensive information on the API functionality and usage is available at <https://gateway.prod.wekeo2.eu/hda-broker/docs>.
License: EUPL (>= 1.2)
Encoding: UTF-8
Imports: R6, httr2, jsonlite, magrittr, htmltools, stringr, humanize
Depends: R (>= 2.10),
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-03 18:49:45 UTC; Mattiuzzi
Author: Matteo Mattiuzzi [aut, cre]
Repository: CRAN
Date/Publication: 2024-09-05 17:30:10 UTC

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New package ggvolcano with initial version 0.1.3
Package: ggvolcano
Title: Publication-Ready Volcano Plots
Version: 0.1.3
Description: Provides publication-ready volcano plots for visualizing differential expression results, commonly used in RNA-seq and similar analyses. This tool helps create high-quality visual representations of data using the 'ggplot2' framework Wickham (2016) <doi:10.1007/978-3-319-24277-4>.
License: MIT + file LICENSE
Imports: config (>= 0.3.2), ggplot2, ggrepel, golem (>= 0.4.1), shiny (>= 1.8.1.1)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-03 15:14:54 UTC; bach
Author: Yaoxiang Li [cre, aut]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2024-09-05 17:10:02 UTC

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New package geoidep with initial version 0.1.0
Package: geoidep
Title: Download Geographic Data on Various Topics Provided and Managed by the Spatial Data Infrastructure of Peru
Version: 0.1.0
Description: Provides R users with easy access to official cartographic data from Peru across a range of topics, including society, transport, environment, agriculture, climate, and more. It also includes data from regional government entities and technical-scientific institutions, all managed by Peru's Spatial Data Infrastructure. For more information, please visit: <https://www.geoidep.gob.pe/catalogos-de-metadatos>.
License: Apache License (>= 2)
URL: https://geografo.pe/geoidep/
BugReports: https://github.com/ambarja/geoidep/issues
Imports: httr, sf, archive
Encoding: UTF-8
Suggests: knitr, rmarkdown, ggplot2, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-03 17:50:53 UTC; USER
Author: antony barja [aut, cre, cph]
Maintainer: antony barja <geografo.pe@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-05 17:20:05 UTC

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New package flowmapblue with initial version 0.0.2
Package: flowmapblue
Title: Flow Map Rendering
Version: 0.0.2
Description: Create interactive flow maps using 'FlowmapBlue' 'TypeScript' library <https://github.com/FlowmapBlue/FlowmapBlue>, which is a free tool for representing aggregated numbers of movements between geographic locations as flow maps. It is used to visualize urban mobility, commuting behavior, bus, subway and air travels, bicycle sharing, human and bird migration, refugee flows, freight transportation, trade, supply chains, scientific collaboration, epidemiological and historical data and many other topics. The package allows to either create standalone flow maps in form of 'htmlwidgets' and save them in 'HTML' files, or integrate flow maps into 'Shiny' applications.
License: MIT + file LICENSE
URL: https://github.com/FlowmapBlue/flowmapblue.R, https://flowmapblue.github.io/flowmapblue.R/
BugReports: https://github.com/FlowmapBlue/flowmapblue.R/issues
Depends: R (>= 2.10)
Imports: htmlwidgets
Suggests: quarto
VignetteBuilder: quarto
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2024-09-03 17:01:04 UTC; ek
Author: Ilya Boyandin [aut, cph] , Egor Kotov [cre]
Maintainer: Egor Kotov <kotov.egor@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-05 17:20:08 UTC

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New package ssw with initial version 0.2.0
Package: ssw
Title: Striped Smith-Waterman Algorithm for Sequence Alignment using SIMD
Version: 0.2.0
Description: Provides an R interface for 'SSW' (Striped Smith-Waterman) via its 'Python' binding 'ssw-py'. 'SSW' is a fast C/C++ implementation of the Smith-Waterman algorithm for pairwise sequence alignment using Single-Instruction-Multiple-Data (SIMD) instructions. 'SSW' enhances the standard algorithm by efficiently returning alignment information and suboptimal alignment scores. The core 'SSW' library offers performance improvements for various bioinformatics tasks, including protein database searches, short-read alignments, primary and split-read mapping, structural variant detection, and read-overlap graph generation. These features make 'SSW' particularly useful for genomic applications. Zhao et al. (2013) <doi:10.1371/journal.pone.0082138> developed the original C/C++ implementation.
License: MIT + file LICENSE
URL: https://nanx.me/ssw-r/, https://github.com/nanxstats/ssw-r
BugReports: https://github.com/nanxstats/ssw-r/issues
Encoding: UTF-8
SystemRequirements: Python (>= 3.6.0), ssw-py (>= 1.0.0). Detailed installation instructions can be found in the README file.
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
Imports: reticulate
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2024-09-01 21:24:13 UTC; nanx
Author: Nan Xiao [aut, cre, cph]
Maintainer: Nan Xiao <me@nanx.me>
Repository: CRAN
Date/Publication: 2024-09-05 16:30:02 UTC

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New package INFOSET with initial version 4.0.5
Package: INFOSET
Title: Computing a New Informative Distribution Set of Asset Returns
Version: 4.0.5
Author: Gloria Polinesi [aut, cre]
Maintainer: Gloria Polinesi <g.polinesi@staff.univpm.it>
Description: Estimation of the most-left informative set of gross returns (i.e., the informative set). The procedure to compute the informative set adjusts the method proposed by Mariani et al. (2022a) <doi:10.1007/s11205-020-02440-6> and Mariani et al. (2022b) <doi:10.1007/s10287-022-00422-2> to gross returns of financial assets. This is accomplished through an adaptive algorithm that identifies sub-groups of gross returns in each iteration by approximating their distribution with a sequence of two-component log-normal mixtures. These sub-groups emerge when a significant change in the distribution occurs below the median of the financial returns, with their boundary termed as the “change point" of the mixture. The process concludes when no further change points are detected. The outcome encompasses parameters of the leftmost mixture distributions and change points of the analyzed financial time series.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Matrix, colorspace, dendextend, quadprog, mixtools, stats, graphics
Depends: R (>= 2.10)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-09-03 14:18:14 UTC; Utente
Repository: CRAN
Date/Publication: 2024-09-05 17:00:02 UTC

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New package GiANT with initial version 1.3.4
Package: GiANT
Title: Gene Set Uncertainty in Enrichment Analysis
Version: 1.3.4
Date: 2024-09-02
Maintainer: Hans A. Kestler <hans.kestler@uni-ulm.de>
Description: Toolbox for various enrichment analysis methods and quantification of uncertainty of gene sets, Schmid et al. (2016) <doi:10.1093/bioinformatics/btw030>.
License: Artistic-2.0
LazyLoad: yes
Depends: R (>= 3.5.0)
Imports: parallel, graphics, grDevices, methods, stats, utils
Suggests: fdrtool, st, limma, globaltest, DESeq2, GlobalAncova
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-03 12:20:46 UTC; julian_schwab
Author: Florian Schmid [aut], Christoph Muessel [aut], Johann M. Kraus [aut], Hans A. Kestler [aut], Hans A. Kestler [cre]
Repository: CRAN
Date/Publication: 2024-09-05 16:50:06 UTC

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New package easybio with initial version 1.0
Package: easybio
Title: Comprehensive Single-Cell Annotation and Transcriptomic Analysis Toolkit
Version: 1.0
Description: Provides a comprehensive toolkit for single-cell annotation with the 'CellMarker2.0' database <http://bio-bigdata.hrbmu.edu.cn/CellMarker/>. Streamlines biological label assignment in single-cell RNA-seq data and facilitates transcriptomic analysis, including preparation of TCGA<https://portal.gdc.cancer.gov/> and GEO<https://www.ncbi.nlm.nih.gov/geo/> datasets, differential expression analysis and visualization of enrichment analysis results. Additional utility functions support various bioinformatics workflows.
URL: https://github.com/person-c/easybio
BugReports: https://github.com/person-c/easybio/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: data.table, ggplot2, limma, R6
Depends: R (>= 2.10)
LazyData: true
Suggests: knitr, patchwork, rmarkdown, ggrepel, Seurat, httr2, GEOquery, fgsea, edgeR, testthat (>= 3.0.0)
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-03 12:36:37 UTC; HUAWEI
Author: Wei Cui [aut, cre, cph]
Maintainer: Wei Cui <m2c.w@outlook.com>
Repository: CRAN
Date/Publication: 2024-09-05 16:50:02 UTC

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New package SuperCell with initial version 1.0
Package: SuperCell
Title: Simplification of scRNA-Seq Data by Merging Together Similar Cells
Version: 1.0
Description: Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells. 'SuperCell' uses 'velocyto.R' <doi:10.1038/s41586-018-0414-6> <https://github.com/velocyto-team/velocyto.R> for RNA velocity. We also recommend installing 'scater' Bioconductor package <doi:10.18129/B9.bioc.scater> <https://bioconductor.org/packages/release/bioc/html/scater.html>.
License: GPL-3
BugReports: https://github.com/GfellerLab/SuperCell/issues
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Additional_repositories: https://mteleman.github.io/drat
Imports: igraph, RANN, WeightedCluster, corpcor, weights, Hmisc, Matrix, matrixStats, plyr, irlba, grDevices, patchwork, ggplot2, umap, entropy, Rtsne, dbscan, scales, plotfunctions, proxy, methods, rlang,
Suggests: SingleCellExperiment, SummarizedExperiment, cowplot, scater, Seurat, knitr, rmarkdown, remotes, bluster, velocyto.R, testthat (>= 3.0.0)
Depends: R (>= 4.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-02 08:28:23 UTC; admin
Author: Mariia Bilous [aut], Leonard Herault [cre]
Maintainer: Leonard Herault <leonard.herault@unil.ch>
Repository: CRAN
Date/Publication: 2024-09-05 15:30:02 UTC

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New package iTOS with initial version 1.0.3
Package: iTOS
Title: Methods and Examples from Introduction to the Theory of Observational Studies
Version: 1.0.3
Author: Paul R. Rosenbaum [aut, cre]
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>
Description: Supplements for a book, "iTOS" = "Introduction to the Theory of Observational Studies." Data sets are 'aHDL' from Rosenbaum (2023a) <doi:10.1111/biom.13558> and 'bingeM' from Rosenbaum (2023b) <doi:10.1111/biom.13921>. The function makematch() uses two-criteria matching from Zhang et al. (2023) <doi:10.1080/01621459.2021.1981337> to create the matched data 'bingeM' from 'binge'. The makematch() function also implements optimal matching (Rosenbaum (1989) <doi:10.2307/2290079>) and matching with fine or near-fine balance (Rosenbaum et al. (2007) <doi:10.1198/016214506000001059> and Yang et al (2012) <doi:10.1111/j.1541-0420.2011.01691.x>). The book makes use of two other R packages, 'weightedRank' and 'tightenBlock'.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: stats, MASS, rcbalance, BiasedUrn, xtable
Suggests: weightedRank
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2024-09-02 19:37:06 UTC; rosenbap
Repository: CRAN
Date/Publication: 2024-09-05 16:00:02 UTC

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New package geoheatmap with initial version 0.1.0
Package: geoheatmap
Title: Create Geospatial Cartogram Heatmaps
Version: 0.1.0
Maintainer: Sanne J.W. Willems <s.j.w.willems@fsw.leidenuniv.nl>
Description: The functionality provided by this package is an expansion of the code of the 'statebins' package, created by B. Rudis (2022), <doi:10.32614/CRAN.package.statebins>. It allows for the creation of square choropleths for the entire world, provided an appropriate specified grid is supplied.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: geofacet, statebins, ggplot2, plotly, rlang
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, viridisLite, testthat (>= 3.0.0), htmltools
LazyData: true
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2024-09-02 13:14:32 UTC; Maria
Author: Sanne J.W. Willems [cre, aut], Maria Rados [aut], Juan Claramunt Gonzalez [ctb]
Repository: CRAN
Date/Publication: 2024-09-05 15:40:02 UTC

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New package ecpdist with initial version 0.2.1
Package: ecpdist
Version: 0.2.1
Date: 2024-08-29
Title: Extended Chen-Poisson Lifetime Distribution
Maintainer: Ana Abreu <abreu@staff.uma.pt>
Suggests: testthat (>= 3.0.0)
Description: Computes the Extended Chen-Poisson (ecp) distribution, survival, density, hazard, cumulative hazard and quantile functions. It also allows to generate a pseudo-random sample from this distribution. The corresponding graphics are available. Functions to obtain measures of skewness and kurtosis, k-th raw moments, conditional k-th moments and mean residual life function were added. For details about ecp distribution, see Sousa-Ferreira, I., Abreu, A.M. & Rocha, C. (2023). <doi:10.57805/revstat.v21i2.405>.
License: GPL-3
URL: <https://github.com/abreu-uma/ecpdist>
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-02 08:52:26 UTC; anaab
Author: Ana Abreu [aut, cre, cph] , Ivo Sousa-Ferreira [aut] , Cristina Rocha [ctb]
Repository: CRAN
Date/Publication: 2024-09-05 15:40:05 UTC

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New package AIFFtools with initial version 1.0
Package: AIFFtools
Title: Read AIFF Files and Convert to WAVE Format
Version: 1.0
Date: 2024-08-20-
Description: Functions are provided to read and convert AIFF audio files to WAVE (WAV) format. This supports, for example, use of the 'tuneR' package, which does not currently handle AIFF files. The AIFF file format is defined in <https://web.archive.org/web/20080125221040/http://www.borg.com/~jglatt/tech/aiff.htm> and <https://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/AIFF/Docs/AIFF-1.3.pdf> .
License: LGPL-3
Imports: R.utils, methods, tuneR
NeedsCompilation: no
Packaged: 2024-09-02 15:08:37 UTC; cgw
Author: Carl Witthoft [aut, cre]
Maintainer: Carl Witthoft <cellocgw@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-05 15:50:02 UTC

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Package spatstat.Knet updated to version 3.1-2 with previous version 3.1-0 dated 2024-07-19

Title: Extension to 'spatstat' for Large Datasets on a Linear Network
Description: Extension to the 'spatstat' family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019).
Author: Suman Rakshit [aut, cph] , Adrian Baddeley [cre, cph]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.Knet versions 3.1-0 dated 2024-07-19 and 3.1-2 dated 2024-09-05

 DESCRIPTION       |    8 +-
 MD5               |   15 ++---
 NEWS              |   14 +++++
 build/partial.rdb |binary
 src/Knet.c        |    4 +
 src/KnetInhom.c   |    3 +
 src/memory.h      |only
 src/netKcode.h    |  150 +++++++++++++++++++++++++++---------------------------
 src/netbase.c     |   25 ++++-----
 9 files changed, 121 insertions(+), 98 deletions(-)

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Package PNAR updated to version 1.7 with previous version 1.6 dated 2023-10-09

Title: Poisson Network Autoregressive Models
Description: Quasi likelihood-based methods for estimating linear and log-linear Poisson Network Autoregression models with p lags and covariates. Tools for testing the linearity versus several non-linear alternatives. Tools for simulation of multivariate count distributions, from linear and non-linear PNAR models, by using a specific copula construction. References include: Armillotta, M. and K. Fokianos (2023). "Nonlinear network autoregression". Annals of Statistics, 51(6): 2526--2552. <doi:10.1214/23-AOS2345>. Armillotta, M. and K. Fokianos (2024). "Count network autoregression". Journal of Time Series Analysis, 45(4): 584--612. <doi:10.1111/jtsa.12728>. Armillotta, M., Tsagris, M. and Fokianos, K. (2024). "Inference for Network Count Time Series with the R Package PNAR". The R Journal, 15/4: 255--269. <doi:10.32614/RJ-2023-094>.
Author: Michail Tsagris [aut, cre], Mirko Armillotta [aut, cph], Konstantinos Fokianos [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between PNAR versions 1.6 dated 2023-10-09 and 1.7 dated 2024-09-05

 DESCRIPTION                       |   12 ++++----
 MD5                               |   52 +++++++++++++++++++-------------------
 man/PNAR-package.Rd               |   20 +++++++++-----
 man/adja.Rd                       |    2 -
 man/adja_gnp.Rd                   |    2 -
 man/crime.Rd                      |    2 -
 man/crime_W.Rd                    |    2 -
 man/global_optimise_LM_stnarpq.Rd |   15 +++-------
 man/global_optimise_LM_tnarpq.Rd  |   17 ++++--------
 man/lin_estimnarpq.Rd             |    9 ++----
 man/lin_ic_plot.Rd                |    7 +++--
 man/lin_narpq_init.Rd             |    9 ++++--
 man/log_lin_estimnarpq.Rd         |    9 ++----
 man/log_lin_ic_plot.Rd            |    7 +++--
 man/log_lin_narpq_init.Rd         |    7 +++--
 man/poisson.MODpq.Rd              |   11 +++++---
 man/poisson.MODpq.log.Rd          |   11 +++++---
 man/poisson.MODpq.nonlin.Rd       |   13 ++++-----
 man/poisson.MODpq.stnar.Rd        |   13 ++++-----
 man/poisson.MODpq.tnar.Rd         |   13 ++++-----
 man/score_test_nonlinpq_h0.Rd     |   13 ++-------
 man/score_test_stnarpq_DV.Rd      |   17 ++++--------
 man/score_test_stnarpq_j.Rd       |   15 +++-------
 man/score_test_tnarpq_j.Rd        |   17 ++++--------
 man/summary.DV.Rd                 |   13 +--------
 man/summary.PNAR.Rd               |    7 -----
 man/summary.nonlin.Rd             |   11 --------
 27 files changed, 146 insertions(+), 180 deletions(-)

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Package osmapiR updated to version 0.2.1 with previous version 0.1.0 dated 2024-06-28

Title: 'OpenStreetMap' API
Description: Interface to 'OpenStreetMap API' for fetching and saving data from/to the 'OpenStreetMap' database (<https://wiki.openstreetmap.org/wiki/API_v0.6>).
Author: Joan Maspons [aut, cre, cph] , Jon Harmon [rev] , Carlos Camara [rev]
Maintainer: Joan Maspons <joanmaspons@gmail.com>

Diff between osmapiR versions 0.1.0 dated 2024-06-28 and 0.2.1 dated 2024-09-05

 osmapiR-0.1.0/osmapiR/tests/testthat/mock_full_object_json                                                     |only
 osmapiR-0.2.1/osmapiR/DESCRIPTION                                                                              |   16 
 osmapiR-0.2.1/osmapiR/MD5                                                                                      |  187 -
 osmapiR-0.2.1/osmapiR/NAMESPACE                                                                                |    6 
 osmapiR-0.2.1/osmapiR/NEWS.md                                                                                  |   39 
 osmapiR-0.2.1/osmapiR/R/import-standalone-s3-register.R                                                        |only
 osmapiR-0.2.1/osmapiR/R/osm_get_changesets.R                                                                   |   27 
 osmapiR-0.2.1/osmapiR/R/osm_get_gpx_metadata.R                                                                 |   24 
 osmapiR-0.2.1/osmapiR/R/osm_get_notes.R                                                                        |   25 
 osmapiR-0.2.1/osmapiR/R/osm_get_objects.R                                                                      |   68 
 osmapiR-0.2.1/osmapiR/R/osm_get_points_gps.R                                                                   |   50 
 osmapiR-0.2.1/osmapiR/R/osm_get_user_details.R                                                                 |   32 
 osmapiR-0.2.1/osmapiR/R/osm_query_changesets.R                                                                 |   37 
 osmapiR-0.2.1/osmapiR/R/osmapiR-package.R                                                                      |    5 
 osmapiR-0.2.1/osmapiR/R/osmapiR_connection.R                                                                   |    8 
 osmapiR-0.2.1/osmapiR/R/osmapiR_methods.R                                                                      |   37 
 osmapiR-0.2.1/osmapiR/R/osmapiR_request.R                                                                      |    2 
 osmapiR-0.2.1/osmapiR/R/osmapi_changesets.R                                                                    |    9 
 osmapiR-0.2.1/osmapiR/R/osmapi_elements.R                                                                      |   15 
 osmapiR-0.2.1/osmapiR/R/osmapi_gps_traces.R                                                                    |   89 
 osmapiR-0.2.1/osmapiR/R/osmapi_map_notes.R                                                                     |   40 
 osmapiR-0.2.1/osmapiR/R/osmapi_user_data.R                                                                     |    5 
 osmapiR-0.2.1/osmapiR/R/osmchange.R                                                                            |    7 
 osmapiR-0.2.1/osmapiR/R/st_as_sf.R                                                                             |only
 osmapiR-0.2.1/osmapiR/R/tags_list-wide.r                                                                       |   24 
 osmapiR-0.2.1/osmapiR/R/xml_to_R.R                                                                             |  215 +
 osmapiR-0.2.1/osmapiR/R/zzz.R                                                                                  |   13 
 osmapiR-0.2.1/osmapiR/README.md                                                                                |   89 
 osmapiR-0.2.1/osmapiR/inst/CITATION                                                                            |only
 osmapiR-0.2.1/osmapiR/inst/WORDLIST                                                                            |   77 
 osmapiR-0.2.1/osmapiR/inst/doc/how_to_edit_gps_traces.html                                                     |    2 
 osmapiR-0.2.1/osmapiR/inst/doc/how_to_edit_osm.html                                                            |    2 
 osmapiR-0.2.1/osmapiR/inst/doc/osmapiR.html                                                                    |   17 
 osmapiR-0.2.1/osmapiR/man/figures/logo.svg                                                                     |  886 +++---
 osmapiR-0.2.1/osmapiR/man/osm_diff_upload_changeset.Rd                                                         |    3 
 osmapiR-0.2.1/osmapiR/man/osm_download_changeset.Rd                                                            |    2 
 osmapiR-0.2.1/osmapiR/man/osm_get_changesets.Rd                                                                |    9 
 osmapiR-0.2.1/osmapiR/man/osm_get_data_gpx.Rd                                                                  |   26 
 osmapiR-0.2.1/osmapiR/man/osm_get_gpx_metadata.Rd                                                              |    8 
 osmapiR-0.2.1/osmapiR/man/osm_get_notes.Rd                                                                     |    9 
 osmapiR-0.2.1/osmapiR/man/osm_get_objects.Rd                                                                   |    2 
 osmapiR-0.2.1/osmapiR/man/osm_get_points_gps.Rd                                                                |   20 
 osmapiR-0.2.1/osmapiR/man/osm_get_user_details.Rd                                                              |    2 
 osmapiR-0.2.1/osmapiR/man/osm_history_object.Rd                                                                |    2 
 osmapiR-0.2.1/osmapiR/man/osm_list_gpxs.Rd                                                                     |    9 
 osmapiR-0.2.1/osmapiR/man/osm_query_changesets.Rd                                                              |    9 
 osmapiR-0.2.1/osmapiR/man/osm_read_bbox_notes.Rd                                                               |    7 
 osmapiR-0.2.1/osmapiR/man/osm_search_notes.Rd                                                                  |    9 
 osmapiR-0.2.1/osmapiR/man/osmapiR-package.Rd                                                                   |   13 
 osmapiR-0.2.1/osmapiR/man/osmchange_delete.Rd                                                                  |    2 
 osmapiR-0.2.1/osmapiR/man/osmchange_modify.Rd                                                                  |    2 
 osmapiR-0.2.1/osmapiR/man/st_as_sf.Rd                                                                          |only
 osmapiR-0.2.1/osmapiR/man/tags_list-wide.Rd                                                                    |    8 
 osmapiR-0.2.1/osmapiR/tests/testthat/_snaps/changesets.md                                                      |  150 +
 osmapiR-0.2.1/osmapiR/tests/testthat/_snaps/elements.md                                                        | 1274 +++++++---
 osmapiR-0.2.1/osmapiR/tests/testthat/_snaps/map_notes.md                                                       |  182 +
 osmapiR-0.2.1/osmapiR/tests/testthat/_snaps/miscellaneous.md                                                   |  929 -------
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_bbox_objects/osm.org/api/0.6/map-e6e175.xml                          |  384 +--
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_bbox_objects/osm.org/api/0.6/map.json-e6e175.json                    |only
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_bbox_objects_empty/osm.org/api/0.6/map-11a636.xml                    |    2 
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_bbox_objects_empty/osm.org/api/0.6/map.json-11a636.json              |only
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_full_object/osm.org/api/0.6/nodes-41cde1.xml                         |    2 
 osmapiR-0.2.1/osmapiR/tests/testthat/mock_full_object/osm.org/api/0.6/nodes.json-41cde1.json                   |only
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Package huito updated to version 0.2.5 with previous version 0.2.4 dated 2023-10-25

Title: Reproducible and Flexible Label Design
Description: An open-source R package to deploys reproducible and flexible labels using layers. The 'huito' package is part of the 'inkaverse' project for developing different procedures and tools used in plant science and experimental designs. Learn more about the 'inkaverse' project at <https://inkaverse.com/>.
Author: Flavio Lozano-Isla [aut, cre] , Inkaverse [cph]
Maintainer: Flavio Lozano-Isla <flozanoisla@gmail.com>

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Package DatastreamDSWS2R updated to version 1.9.10 with previous version 1.9.7 dated 2024-01-15

Title: Provides a Link Between the 'LSEG Datastream' System and R
Description: Provides a set of functions and a class to connect, extract and upload information from the 'LSEG Datastream' database. This package uses the 'DSWS' API and server used by the 'Datastream DFO addin'. Details of this API are available at <https://www.lseg.com/en/data-analytics>. Please report issues at <https://github.com/CharlesCara/DatastreamDSWS2R/issues>.
Author: Charles Cara [aut, cre]
Maintainer: Charles Cara <charles.cara@absolute-strategy.com>

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Package connectapi updated to version 0.3.0 with previous version 0.2.0 dated 2024-06-06

Title: Utilities for Interacting with the 'Posit Connect' Server API
Description: Provides a helpful 'R6' class and methods for interacting with the 'Posit Connect' Server API along with some meaningful utility functions for regular tasks. API documentation varies by 'Posit Connect' installation and version, but the latest documentation is also hosted publicly at <https://docs.posit.co/connect/api/>.
Author: Toph Allen [aut, cre], Neal Richardson [aut], Sean Lopp [aut], Cole Arendt [aut], Posit, PBC [cph, fnd]
Maintainer: Toph Allen <toph@posit.co>

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Package CALANGO updated to version 1.0.20 with previous version 1.0.16 dated 2023-04-26

Title: Comparative Analysis with Annotation-Based Genomic Components
Description: A first-principle, phylogeny-aware comparative genomics tool for investigating associations between terms used to annotate genomic components (e.g., Pfam IDs, Gene Ontology terms,) with quantitative or rank variables such as number of cell types, genome size, or density of specific genomic elements. See the project website for more information, documentation and examples, and <doi:10.1016/j.patter.2023.100728> for the full paper.
Author: Francisco Lobo [aut], Felipe Campelo [aut, cre], Jorge Augusto Hongo [aut], Giovanni Marques de Castro [aut], Gabriel Almeida [sad, dnc]
Maintainer: Felipe Campelo <fcampelo@gmail.com>

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Package occCite updated to version 0.5.8 with previous version 0.5.7 dated 2024-06-23

Title: Querying and Managing Large Biodiversity Occurrence Datasets
Description: Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.
Author: Hannah L. Owens [aut, cre] , Cory Merow [aut] , Brian Maitner [aut] , Jamie M. Kass [aut] , Vijay Barve [aut] , Robert P. Guralnick [aut] , Damiano Oldoni [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/407>)
Maintainer: Hannah L. Owens <hannah.owens@gmail.com>

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Package gstat updated to version 2.1-2 with previous version 2.1-1 dated 2023-04-06

Title: Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation
Description: Variogram modelling; simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions; supports sf and stars.
Author: Edzer Pebesma [aut, cre] , Benedikt Graeler [aut]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package wordmap updated to version 0.9.0 with previous version 0.8.0 dated 2024-06-18

Title: Feature Extraction and Document Classification with Noisy Labels
Description: Extract features and classify documents with noisy labels given by document-meta data or keyword matching Watanabe & Zhou (2020) <doi:10.1177/0894439320907027>.
Author: Kohei Watanabe [aut, cre, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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Package seededlda updated to version 1.4.0 with previous version 1.3.2 dated 2024-07-03

Title: Seeded Sequential LDA for Topic Modeling
Description: Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) <doi:10.1177/08944393231178605>. Implements Seeded LDA (Lu et al., 2010) <doi:10.1109/ICDMW.2011.125> and Sequential LDA (Du et al., 2012) <doi:10.1007/s10115-011-0425-1> with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing.
Author: Kohei Watanabe [aut, cre, cph], Phan Xuan-Hieu [aut, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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Package hdnom updated to version 6.0.4 with previous version 6.0.3 dated 2024-03-02

Title: Benchmarking and Visualization Toolkit for Penalized Cox Models
Description: Creates nomogram visualizations for penalized Cox regression models, with the support of reproducible survival model building, validation, calibration, and comparison for high-dimensional data.
Author: Nan Xiao [aut, cre] , Qing-Song Xu [aut], Miao-Zhu Li [aut], Frank Harrell [ctb] , Sergej Potapov [ctb] , Werner Adler [ctb] , Matthias Schmid [ctb]
Maintainer: Nan Xiao <me@nanx.me>

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Package georob updated to version 0.3-20 with previous version 0.3-19 dated 2024-03-10

Title: Robust Geostatistical Analysis of Spatial Data
Description: Provides functions for efficiently fitting linear models with spatially correlated errors by robust (Kuensch et al. (2011) <doi:10.3929/ethz-a-009900710>) and Gaussian (Harville (1977) <doi:10.1080/01621459.1977.10480998>) (Restricted) Maximum Likelihood and for computing robust and customary point and block external-drift Kriging predictions (Cressie (1993) <doi:10.1002/9781119115151>), along with utility functions for variogram modelling in ad hoc geostatistical analyses, model building, model evaluation by cross-validation, (conditional) simulation of Gaussian processes (Davies and Bryant (2013) <doi:10.18637/jss.v055.i09>), unbiased back-transformation of Kriging predictions of log-transformed data (Cressie (2006) <doi:10.1007/s11004-005-9022-8>).
Author: Andreas Papritz [aut, cre]
Maintainer: Andreas Papritz <papritz@retired.ethz.ch>

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Package garma updated to version 0.9.22 with previous version 0.9.20 dated 2024-08-23

Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Description: Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) <doi:10.1007/s00362-022-01290-3>. Refer to the vignette for details of fitting these processes.
Author: Richard Hunt [aut, cre]
Maintainer: Richard Hunt <maint@huntemail.id.au>

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Package spatstat.univar updated to version 3.0-1 with previous version 3.0-0 dated 2024-06-28

Title: One-Dimensional Probability Distribution Support for the 'spatstat' Family
Description: Estimation of one-dimensional probability distributions including kernel density estimation, weighted empirical cumulative distribution functions, Kaplan-Meier and reduced-sample estimators for right-censored data, heat kernels, kernel properties, quantiles and integration.
Author: Adrian Baddeley [aut, cre, cph] , Tilman M. Davies [aut, ctb, cph] , Martin L. Hazelton [aut, ctb, cph] , Ege Rubak [aut, cph] , Rolf Turner [aut, cph] , Greg McSwiggan [ctb, cph]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package scoringRules updated to version 1.1.2 with previous version 1.1.1 dated 2023-05-10

Title: Scoring Rules for Parametric and Simulated Distribution Forecasts
Description: Dictionary-like reference for computing scoring rules in a wide range of situations. Covers both parametric forecast distributions (such as mixtures of Gaussians) and distributions generated via simulation. Further details can be found in the package vignettes <doi:10.18637/jss.v090.i12>, <doi:10.18637/jss.v110.i08>.
Author: Alexander I. Jordan [aut] , Fabian Krueger [aut, cre] , Sebastian Lerch [aut] , Sam Allen [aut] , Maximiliane Graeter [ctb]
Maintainer: Fabian Krueger <Fabian.Krueger83@gmail.com>

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Package reticulate updated to version 1.39.0 with previous version 1.38.0 dated 2024-06-19

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Tomasz Kalinowski [ctb, cre], Kevin Ushey [aut], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] , Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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Package DRDID updated to version 1.1.0 with previous version 1.0.7 dated 2024-07-05

Title: Doubly Robust Difference-in-Differences Estimators
Description: Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) <doi:10.1016/j.jeconom.2020.06.003>. The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.
Author: Pedro H. C. Sant'Anna [aut, cre, cph], Jun Zhao [aut]
Maintainer: Pedro H. C. Sant'Anna <pedrosantanna@causal-solutions.com>

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Package Kira updated to version 1.0.6 with previous version 1.0.5 dated 2024-07-05

Title: Machine Learning
Description: Machine learning, containing several algorithms for supervised and unsupervised classification, in addition to a function that plots the Receiver Operating Characteristic (ROC) and Precision-Recall (PRC) curve graphs, and also a function that returns several metrics used for model evaluation, the latter can be used in ranking results from other packs.
Author: Paulo Cesar Ossani [aut, cre]
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

Diff between Kira versions 1.0.5 dated 2024-07-05 and 1.0.6 dated 2024-09-05

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Package bggAnalytics (with last version 0.2.1) was removed from CRAN

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

2022-08-31 0.2.1
2021-09-23 0.2.0
2020-10-22 0.1.1

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Package cregg (with last version 0.4.0) was removed from CRAN

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

2020-06-28 0.4.0
2018-07-30 0.3.0

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New package optimCheck with initial version 1.0.1
Package: optimCheck
Title: Graphical and Numerical Checks for Mode-Finding Routines
Version: 1.0.1
Date: 2024-09-04
Description: Tools for checking that the output of an optimization algorithm is indeed at a local mode of the objective function. This is accomplished graphically by calculating all one-dimensional "projection plots" of the objective function, i.e., varying each input variable one at a time with all other elements of the potential solution being fixed. The numerical values in these plots can be readily extracted for the purpose of automated and systematic unit-testing of optimization routines.
URL: https://github.com/mlysy/optimCheck
BugReports: https://github.com/mlysy/optimCheck/issues
License: GPL-3
Imports: stats, graphics
Encoding: UTF-8
Suggests: testthat, quantreg, mclust, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-04 20:02:50 UTC; mlysy
Author: Martin Lysy [aut, cre]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>
Repository: CRAN
Date/Publication: 2024-09-05 05:00:02 UTC

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Package LocaTT updated to version 1.1.2 with previous version 1.1.1 dated 2023-10-30

Title: Geographically-Conscious Taxonomic Assignment for Metabarcoding
Description: A bioinformatics pipeline for performing taxonomic assignment of DNA metabarcoding sequence data while considering geographic location. A detailed tutorial is available at <https://urodelan.github.io/Local_Taxa_Tool_Tutorial/>. A manuscript describing these methods is in preparation.
Author: Kenen Goodwin [aut, cre] , Taal Levi [aut]
Maintainer: Kenen Goodwin <urodelan@gmail.com>

Diff between LocaTT versions 1.1.1 dated 2023-10-30 and 1.1.2 dated 2024-09-05

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Package PopVar (with last version 1.3.1) was removed from CRAN

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

2024-01-29 1.3.1

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Package ModTools (with last version 0.9.12) was removed from CRAN

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

2024-07-31 0.9.12
2024-01-23 0.9.6
2021-07-26 0.9.4

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