Tue, 30 Sep 2025

Package dominanceanalysis updated to version 2.1.1 with previous version 2.1.0 dated 2024-02-05

Title: Dominance Analysis
Description: Dominance analysis is a method that allows to compare the relative importance of predictors in multiple regression models: ordinary least squares, generalized linear models, hierarchical linear models, beta regression and dynamic linear models. The main principles and methods of dominance analysis are described in Budescu, D. V. (1993) <doi:10.1037/0033-2909.114.3.542> and Azen, R., & Budescu, D. V. (2003) <doi:10.1037/1082-989X.8.2.129> for ordinary least squares regression. Subsequently, the extensions for multivariate regression, logistic regression and hierarchical linear models were described in Azen, R., & Budescu, D. V. (2006) <doi:10.3102/10769986031002157>, Azen, R., & Traxel, N. (2009) <doi:10.3102/1076998609332754> and Luo, W., & Azen, R. (2013) <doi:10.3102/1076998612458319>, respectively.
Author: Claudio Bustos Navarrete [aut, cre, cph] , Filipa Coutinho Soares [aut]
Maintainer: Claudio Bustos Navarrete <clbustos@gmail.com>

Diff between dominanceanalysis versions 2.1.0 dated 2024-02-05 and 2.1.1 dated 2025-09-30

 DESCRIPTION                                    |   17 ++++---
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 15 files changed, 78 insertions(+), 72 deletions(-)

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Package COINT updated to version 0.0.2 with previous version 0.0.1 dated 2025-09-08

Title: Unit Root Tests with Structural Breaks and Fully-Modified Estimators
Description: Procedures include Phillips (1995) FMVAR <doi:10.2307/2171721>, Kitamura and Phillips (1997) FMGMM <doi:10.1016/S0304-4076(97)00004-3>, Park (1992) CCR <doi:10.2307/2951679>, and so on. Tests with 1 or 2 structural breaks include Gregory and Hansen (1996) <doi:10.1016/0304-4076(69)41685-7>, Zivot and Andrews (1992) <doi:10.2307/1391541>, and Kurozumi (2002) <doi:10.1016/S0304-4076(01)00106-3>.
Author: Ho Tsung-wu [aut, cre]
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

Diff between COINT versions 0.0.1 dated 2025-09-08 and 0.0.2 dated 2025-09-30

 DESCRIPTION      |   10 -
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Package tiledb updated to version 0.33.0 with previous version 0.32.0 dated 2025-05-15

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], Isaiah Norton [cre]
Maintainer: Isaiah Norton <isaiah@tiledb.com>

Diff between tiledb versions 0.32.0 dated 2025-05-15 and 0.33.0 dated 2025-09-30

 DESCRIPTION                                         |    6 
 LICENSE                                             |    2 
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 NEWS.md                                             |   25 
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Package GDILM.SEIRS updated to version 0.0.4 with previous version 0.0.3 dated 2025-01-13

Title: Spatial Modeling of Infectious Disease with Reinfection
Description: Geographically Dependent Individual Level Models (GDILMs) within the Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework are applied to model infectious disease transmission, incorporating reinfection dynamics. This package employs a likelihood based Monte Carlo Expectation Conditional Maximization (MCECM) algorithm for estimating model parameters. It also provides tools for GDILM fitting, parameter estimation, AIC calculation on real pandemic data, and simulation studies customized to user-defined model settings.
Author: Amin Abed [aut, cre, cph] , Mahmoud Torabi [ths], Zeinab Mashreghi [ths]
Maintainer: Amin Abed <abeda@myumanitoba.ca>

Diff between GDILM.SEIRS versions 0.0.3 dated 2025-01-13 and 0.0.4 dated 2025-09-30

 DESCRIPTION                                   |    9 +++++----
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 5 files changed, 14 insertions(+), 13 deletions(-)

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Package SSN2 updated to version 0.3.1 with previous version 0.3.0 dated 2025-08-18

Title: Spatial Modeling on Stream Networks
Description: Spatial statistical modeling and prediction for data on stream networks, including models based on in-stream distance (Ver Hoef, J.M. and Peterson, E.E., (2010) <DOI:10.1198/jasa.2009.ap08248>.) Models are created using moving average constructions. Spatial linear models, including explanatory variables, can be fit with (restricted) maximum likelihood. Mapping and other graphical functions are included.
Author: Michael Dumelle [aut, cre] , Jay M. Ver Hoef [aut], Erin Peterson [aut], Alan Pearse [ctb], Dan Isaak [ctb]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

Diff between SSN2 versions 0.3.0 dated 2025-08-18 and 0.3.1 dated 2025-09-30

 DESCRIPTION               |   10 -
 MD5                       |    8 -
 NEWS.md                   |    7 
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 5 files changed, 184 insertions(+), 174 deletions(-)

More information about SSN2 at CRAN
Permanent link

Package RcppEnsmallen updated to version 0.3.10.0.1 with previous version 0.2.22.1.2 dated 2025-09-10

Title: Header-Only C++ Mathematical Optimization Library for 'Armadillo'
Description: 'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++14 [...truncated...]
Author: James Joseph Balamuta [aut, cre, cph] , Dirk Eddelbuettel [aut, cph]
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

Diff between RcppEnsmallen versions 0.2.22.1.2 dated 2025-09-10 and 0.3.10.0.1 dated 2025-09-30

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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/ChangeLog                                                                              |    7 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/DESCRIPTION                                                                            |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/MD5                                                                                    |  398 +++++-----
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/NEWS.md                                                                                |   60 +
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/ada_grad/ada_grad.hpp                                      |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/ada_grad/ada_grad_update.hpp                               |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/ada_sqrt/ada_sqrt.hpp                                      |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/ada_sqrt/ada_sqrt_update.hpp                               |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/adam/adam.hpp                                              |    2 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/callbacks/timer_stop.hpp                                   |   27 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/cd/cd.hpp                                                  |    2 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/de/de.hpp                                                  |    8 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/demon_adam/demon_adam.hpp                                  |   10 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/ens_version.hpp                                            |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/eve/eve.hpp                                                |    2 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/function/arma_traits.hpp                                   |   24 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/fw/atoms.hpp                                               |    1 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/iqn/iqn.hpp                                                |    6 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/katyusha/katyusha.hpp                                      |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/katyusha/katyusha_impl.hpp                                 |   30 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/lbfgs/lbfgs.hpp                                            |   15 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/lbfgs/lbfgs_impl.hpp                                       |  147 ++-
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/lookahead/lookahead.hpp                                    |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/lookahead/lookahead_impl.hpp                               |   36 
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 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/moead/moead_impl.hpp                                       |  237 +++--
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/moead/weight_init_policies/bbs_init.hpp                    |   10 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/moead/weight_init_policies/dirichlet_init.hpp              |   15 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/moead/weight_init_policies/uniform_init.hpp                |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/nsga2/nsga2.hpp                                            |  148 +--
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/nsga2/nsga2_impl.hpp                                       |  210 +++--
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/padam/padam_update.hpp                                     |   53 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/parallel_sgd/parallel_sgd_impl.hpp                         |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/ackley_function_impl.hpp                          |   17 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/aug_lagrangian_test_functions.hpp                 |   20 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/aug_lagrangian_test_functions_impl.hpp            |   65 +
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/beale_function_impl.hpp                           |   22 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/booth_function_impl.hpp                           |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/colville_function_impl.hpp                        |   20 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/cross_in_tray_function_impl.hpp                   |   10 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/easom_function_impl.hpp                           |   24 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/fonseca_fleming_function.hpp                      |   36 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/generalized_rosenbrock_function.hpp               |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/generalized_rosenbrock_function_impl.hpp          |   40 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/goldstein_price_function_impl.hpp                 |   45 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/gradient_descent_test_function_impl.hpp           |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/himmelblau_function.hpp                           |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/himmelblau_function_impl.hpp                      |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/levy_function_n13.hpp                             |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/levy_function_n13_impl.hpp                        |   33 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/logistic_regression_function.hpp                  |   70 +
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/logistic_regression_function_impl.hpp             |  244 +++---
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf1_function.hpp                             |  243 +++---
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf2_function.hpp                             |  289 +++----
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf3_function.hpp                             |  268 +++---
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf4_function.hpp                             |  295 +++----
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf5_function.hpp                             |  322 +++-----
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/maf/maf6_function.hpp                             |  348 ++++----
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/matyas_function_impl.hpp                          |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/mc_cormick_function_impl.hpp                      |   22 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/problems.hpp                                      |    1 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/quadratic_function.hpp                            |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/quadratic_function_impl.hpp                       |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/rastrigin_function.hpp                            |   10 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/rastrigin_function_impl.hpp                       |   44 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/rosenbrock_function_impl.hpp                      |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/rosenbrock_wood_function.hpp                      |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/rosenbrock_wood_function_impl.hpp                 |    7 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/schaffer_function_n1.hpp                          |   17 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/schaffer_function_n2_impl.hpp                     |   17 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/schaffer_function_n4_impl.hpp                     |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/schwefel_function.hpp                             |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/sgd_test_function_impl.hpp                        |   15 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/softmax_regression_function.hpp                   |   47 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/softmax_regression_function_impl.hpp              |  118 +-
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/sparse_test_function_impl.hpp                     |   20 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/sphere_function.hpp                               |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/sphere_function_impl.hpp                          |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/styblinski_tang_function.hpp                      |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/styblinski_tang_function_impl.hpp                 |   19 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/three_hump_camel_function_impl.hpp                |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/wood_function_impl.hpp                            |   24 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/zdt/zdt1_function.hpp                             |  176 ++--
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/zdt/zdt2_function.hpp                             |    5 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/zdt/zdt3_function.hpp                             |    7 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/zdt/zdt4_function.hpp                             |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/problems/zdt/zdt6_function.hpp                             |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/pso/init_policies/default_init.hpp                         |   22 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/pso/pso.hpp                                                |   19 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/pso/pso_impl.hpp                                           |   46 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/pso/update_policies/lbest_update.hpp                       |  204 ++---
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/qhadam/qhadam.hpp                                          |   10 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/qhadam/qhadam_update.hpp                                   |   40 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/rmsprop/rmsprop.hpp                                        |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/rmsprop/rmsprop_update.hpp                                 |   21 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sa/exponential_schedule.hpp                                |    7 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sa/sa_impl.hpp                                             |   28 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sarah/sarah.hpp                                            |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sarah/sarah_impl.hpp                                       |   13 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sarah/sarah_plus_update.hpp                                |    8 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sarah/sarah_update.hpp                                     |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/lin_alg.hpp                                            |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/lrsdp.hpp                                              |   16 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/lrsdp_function.hpp                                     |   19 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/lrsdp_function_impl.hpp                                |   47 -
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/lrsdp_impl.hpp                                         |   23 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sdp/primal_dual_impl.hpp                                   |   10 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/sgd.hpp                                                |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/sgd_impl.hpp                                           |   19 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/update_policies/momentum_update.hpp                    |   11 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/update_policies/nesterov_momentum_update.hpp           |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/update_policies/quasi_hyperbolic_update.hpp            |   27 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgd/update_policies/vanilla_update.hpp                     |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/cyclical_decay.hpp                                    |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/sgdr.hpp                                              |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/sgdr_impl.hpp                                         |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/snapshot_ensembles.hpp                                |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/snapshot_sgdr.hpp                                     |   36 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/sgdr/snapshot_sgdr_impl.hpp                                |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/smorms3/smorms3.hpp                                        |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/smorms3/smorms3_update.hpp                                 |   36 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/spalera_sgd/spalera_sgd.hpp                                |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/spalera_sgd/spalera_sgd_impl.hpp                           |   13 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/spalera_sgd/spalera_stepsize.hpp                           |   76 +
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/spsa/spsa_impl.hpp                                         |   18 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/svrg/barzilai_borwein_decay.hpp                            |   24 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/svrg/svrg.hpp                                              |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/svrg/svrg_impl.hpp                                         |    6 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/svrg/svrg_update.hpp                                       |    4 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/swats/swats.hpp                                            |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/swats/swats_update.hpp                                     |   78 +
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/detect_callbacks.hpp                               |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/function_traits.hpp                                |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/indicators/epsilon.hpp                             |   85 +-
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/indicators/igd.hpp                                 |  110 +-
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/indicators/igd_plus.hpp                            |   83 +-
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/proxies.hpp                                        |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/utility/using.hpp                                          |only
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/wn_grad/wn_grad.hpp                                        |    2 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/wn_grad/wn_grad_update.hpp                                 |   18 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/yogi/yogi.hpp                                              |   14 
 RcppEnsmallen-0.3.10.0.1/RcppEnsmallen/inst/include/ensmallen_bits/yogi/yogi_update.hpp                                       |   32 
 202 files changed, 4470 insertions(+), 3603 deletions(-)

More information about RcppEnsmallen at CRAN
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Package ModelMap updated to version 3.4.0.8 with previous version 3.4.0.4 dated 2023-04-24

Title: Modeling and Map Production using Random Forest and Related Stochastic Models
Description: Creates sophisticated models of training data and validates the models with an independent test set, cross validation, or Out Of Bag (OOB) predictions on the training data. Create graphs and tables of the model validation results. Applies these models to GIS .img files of predictors to create detailed prediction surfaces. Handles large predictor files for map making, by reading in the .img files in chunks, and output to the .txt file the prediction for each data chunk, before reading the next chunk of data.
Author: Elizabeth Freeman [aut, cre], Tracey Frescino [aut]
Maintainer: Elizabeth Freeman <elizabeth.a.freeman@usda.gov>

Diff between ModelMap versions 3.4.0.4 dated 2023-04-24 and 3.4.0.8 dated 2025-09-30

 DESCRIPTION                  |   20 ++++++++++++++------
 MD5                          |   18 +++++++++---------
 build/vignette.rds           |binary
 inst/CHANGELOG               |   12 ++++++++++--
 inst/doc/ExploreModelMap.pdf |binary
 inst/doc/VModelMap.pdf       |binary
 inst/doc/Vquantile.pdf       |binary
 man/ModelMap-package.Rd      |    4 ++--
 man/model.importance.plot.Rd |    2 +-
 man/model.mapmake.Rd         |    6 +++---
 10 files changed, 39 insertions(+), 23 deletions(-)

More information about ModelMap at CRAN
Permanent link

Package exametrika updated to version 1.6.3 with previous version 1.6.1 dated 2025-08-26

Title: Test Theory Analysis and Biclustering
Description: Implements comprehensive test data engineering methods as described in Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for engineering and processing test data: Classical Test Theory (CTT) with reliability coefficients for continuous ability assessment; Item Response Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank Analysis (LRA) for ordinal clustering with automatic determination of cluster numbers; Biclustering methods including infinite relational models for simultaneous clustering of examinees and items without predefined cluster numbers; and Bayesian Network Models (BNM) for visualizing inter-item dependencies. Features local dependence analysis through LRA and biclustering, parameter estimation, dimensionality assessment, and network structure visualization for educational, psychological, and social science research.
Author: Koji Kosugi [aut, cre]
Maintainer: Koji Kosugi <kosugitti@gmail.com>

Diff between exametrika versions 1.6.1 dated 2025-08-26 and 1.6.3 dated 2025-09-30

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 exametrika-1.6.1/exametrika/man/score_function_with_Jacobian.Rd |only
 exametrika-1.6.1/exametrika/man/target_to_params_jac.Rd         |only
 exametrika-1.6.3/exametrika/DESCRIPTION                         |   18 
 exametrika-1.6.3/exametrika/MD5                                 |   56 -
 exametrika-1.6.3/exametrika/NAMESPACE                           |    3 
 exametrika-1.6.3/exametrika/NEWS.md                             |   36 
 exametrika-1.6.3/exametrika/R/00_EMclus.R                       |    6 
 exametrika-1.6.3/exametrika/R/00_GridSearch.R                   |   96 ++
 exametrika-1.6.3/exametrika/R/00_exametrikaPlot.R               |   20 
 exametrika-1.6.3/exametrika/R/01_dataFormat.R                   |  223 ++++-
 exametrika-1.6.3/exametrika/R/02_TestItemFunctions.R            |   50 -
 exametrika-1.6.3/exametrika/R/05_LCA.R                          |    2 
 exametrika-1.6.3/exametrika/R/06_LRA.R                          |    9 
 exametrika-1.6.3/exametrika/R/07_Biclustering.R                 |   41 -
 exametrika-1.6.3/exametrika/R/12_OrdinalLatentRank.R            |   12 
 exametrika-1.6.3/exametrika/R/13_RatedLatentRank.R              |   12 
 exametrika-1.6.3/exametrika/R/14_GRM.R                          |  391 +---------
 exametrika-1.6.3/exametrika/R/15_NominalBiclustering.R          |    4 
 exametrika-1.6.3/exametrika/R/16_OrdinalBiclustering.R          |    6 
 exametrika-1.6.3/exametrika/R/RcppExports.R                     |only
 exametrika-1.6.3/exametrika/README.md                           |   34 
 exametrika-1.6.3/exametrika/man/Biclustering.Rd                 |    1 
 exametrika-1.6.3/exametrika/man/GRM.Rd                          |    2 
 exametrika-1.6.3/exametrika/man/GridSearch.Rd                   |    2 
 exametrika-1.6.3/exametrika/man/LCA.Rd                          |    1 
 exametrika-1.6.3/exametrika/man/LRA.Rd                          |    3 
 exametrika-1.6.3/exametrika/man/crr.Rd                          |    4 
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 32 files changed, 548 insertions(+), 484 deletions(-)

More information about exametrika at CRAN
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Package writeAlizer updated to version 1.6.5 with previous version 1.6.4 dated 2025-09-30

Title: Generate Predicted Writing Quality Scores
Description: Imports variables from 'ReaderBench' (Dascalu et al., 2018)<doi:10.1007/978-3-319-66610-5_48>, 'Coh-Metrix' (McNamara et al., 2014)<doi:10.1017/CBO9780511894664>, and/or 'GAMET' (Crossley et al., 2019) <doi:10.17239/jowr-2019.11.02.01> output files; downloads predictive scoring models described in Mercer & Cannon (2022)<doi:10.31244/jero.2022.01.03> and Mercer et al.(2021)<doi:10.1177/0829573520987753>; and generates predicted writing quality and curriculum-based measurement (McMaster & Espin, 2007)<doi:10.1177/00224669070410020301> scores.
Author: Sterett H. Mercer [aut, cre]
Maintainer: Sterett H. Mercer <sterett.mercer@ubc.ca>

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Package LearnNonparam updated to version 1.3.0 with previous version 1.2.9 dated 2025-06-02

Title: 'R6'-Based Flexible Framework for Permutation Tests
Description: Implements non-parametric tests from Higgins (2004, ISBN:0534387756), including tests for one sample, two samples, k samples, paired comparisons, blocked designs, trends and association. Built with 'Rcpp' for efficiency and 'R6' for flexible, object-oriented design, the package provides a unified framework for performing or creating custom permutation tests.
Author: Yan Du [aut, cre]
Maintainer: Yan Du <isduyan@outlook.com>

Diff between LearnNonparam versions 1.2.9 dated 2025-06-02 and 1.3.0 dated 2025-09-30

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Package calidad updated to version 0.8.2 with previous version 0.8.1 dated 2025-06-02

Title: Assesses the Quality of Estimates Made by Complex Sample Designs
Description: Assesses the quality of estimates made by complex sample designs, following the methodology developed by the National Institute of Statistics Chile (Household Survey Standard 2020, <https://www.ine.cl/docs/default-source/institucionalidad/buenas-pr%C3%A1cticas/clasificaciones-y-estandares/est%C3%A1ndar-evaluaci%C3%B3n-de-calidad-de-estimaciones-publicaci%C3%B3n-27022020.pdf>), (Economics Survey Standard 2024, <https://www.ine.gob.cl/docs/default-source/buenas-practicas/directrices-metodologicas/estandares/documentos/est%C3%A1ndar-evaluaci%C3%B3n-de-calidad-de-estimaciones-econ%C3%B3micas.pdf?sfvrsn=201fbeb9_2>) and by Economic Commission for Latin America and Caribbean (2020, <https://repositorio.cepal.org/bitstream/handle/11362/45681/1/S2000293_es.pdf>), (2024, <https://repositorio.cepal.org/server/api/core/bitstreams/f04569e6-4f38-42e7-a32b-e0b298e0ab9c/content>).
Author: Klaus Lehmann [aut, cre], Ricardo Pizarro [aut], Ignacio Agloni [ctb], Andrea Lopez [ctb], Javiera Preuss [ctb]
Maintainer: Klaus Lehmann <klehmann@fen.uchile.cl>

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Package bdsm updated to version 0.3.0 with previous version 0.2.2 dated 2025-09-02

Title: Bayesian Dynamic Systems Modeling
Description: Implements methods for building and analyzing models based on panel data as described in the paper by Moral-Benito (2013, <doi:10.1080/07350015.2013.818003>). The package provides functions to estimate dynamic panel data models and analyze the results of the estimation.
Author: Mateusz Wyszynski [aut], Marcin Dubel [ctb, cre], Krzysztof Beck [ctb]
Maintainer: Marcin Dubel <marcindubel@gmail.com>

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Package toxEval updated to version 1.4.1 with previous version 1.4.0 dated 2024-11-22

Title: Exploring Biological Relevance of Environmental Chemistry Observations
Description: Data analysis package for estimating potential biological effects from chemical concentrations in environmental samples. Included are a set of functions to analyze, visualize, and organize measured concentration data as it relates to user-selected chemical-biological interaction benchmark data such as water quality criteria. The intent of these analyses is to develop a better understanding of the potential biological relevance of environmental chemistry data. Results can be used to prioritize which chemicals at which sites may be of greatest concern. These methods are meant to be used as a screening technique to predict potential for biological influence from chemicals that ultimately need to be validated with direct biological assays. A description of the analysis can be found in Blackwell (2017) <doi:10.1021/acs.est.7b01613>.
Author: Laura DeCicco [aut, cre] , Steven Corsi [aut] , Daniel Villeneuve [aut] , Brett Blackwell [aut] , Gerald Ankley [aut] , Alison Appling [rev] , Dalma Martinovic [rev]
Maintainer: Laura DeCicco <ldecicco@usgs.gov>

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Package skpr updated to version 1.9.2 with previous version 1.9.0 dated 2025-09-16

Title: Design of Experiments Suite: Generate and Evaluate Optimal Designs
Description: Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible. For details, see Morgan-Wall et al. (2021) <doi:10.18637/jss.v099.i01>.
Author: Tyler Morgan-Wall [aut, cre], George Khoury [aut]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package phm updated to version 2.1.2 with previous version 1.1.4 dated 2025-05-16

Title: Phrase Mining
Description: Functions to extract and handle commonly occurring principal phrases obtained from collections of texts. Major speed improvements - core functions rewritten in C++ for faster phrase-document parsing, clustering, and text distance computations. Based on, Small, E., & Cabrera, J. (2025). Principal phrase mining, an automated method for extracting meaningful phrases from text. International Journal of Computers and Applications, 47(1), 84–92.
Author: Ellie Small [aut, cre]
Maintainer: Ellie Small <ellie_small@yahoo.com>

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Package speakeasyR updated to version 0.1.8 with previous version 0.1.7 dated 2025-09-05

Title: Fast and Robust Multi-Scale Graph Clustering
Description: A graph community detection algorithm that aims to be performant on large graphs and robust, returning consistent results across runs. SpeakEasy 2 (SE2), the underlying algorithm, is described in Chris Gaiteri, David R. Connell & Faraz A. Sultan et al. (2023) <doi:10.1186/s13059-023-03062-0>. The core algorithm is written in 'C', providing speed and keeping the memory requirements low. This implementation can take advantage of multiple computing cores without increasing memory usage. SE2 can detect community structure across scales, making it a good choice for biological data, which often has hierarchical structure. Graphs can be passed to the algorithm as adjacency matrices using base 'R' matrices, the 'Matrix' library, 'igraph' graphs, or any data that can be coerced into a matrix.
Author: David Connell [aut, cre, cph] , Chris Gaiteri [cph] , Gabor Csardi [cph, ctb] , Tamas Nepusz [cph, ctb] , Szabolcs Horvat [cph, ctb] , Vincent Traag [cph, ctb] , Fabio Zanini [cph, ctb] , Daniel Noom [cph, ctb] , The igraph development team [cph] , F [...truncated...]
Maintainer: David Connell <david32@dcon.addy.io>

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 speakeasyR-0.1.8/speakeasyR/DESCRIPTION                                                           |    6 
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 speakeasyR-0.1.8/speakeasyR/NEWS.md                                                               |   17 
 speakeasyR-0.1.8/speakeasyR/R/cluster.R                                                           |   28 
 speakeasyR-0.1.8/speakeasyR/R/cluster_genes.R                                                     |    3 
 speakeasyR-0.1.8/speakeasyR/R/knn_graph.R                                                         |   12 
 speakeasyR-0.1.8/speakeasyR/R/order_nodes.R                                                       |   22 
 speakeasyR-0.1.8/speakeasyR/R/utils.R                                                             |   16 
 speakeasyR-0.1.8/speakeasyR/configure                                                             |   19 
 speakeasyR-0.1.8/speakeasyR/configure.ac                                                          |    3 
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 speakeasyR-0.1.8/speakeasyR/src/include/igraph_config.h                                           |    4 
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 speakeasyR-0.1.8/speakeasyR/src/se2/CMakeLists.txt                                                |    3 
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 speakeasyR-0.1.8/speakeasyR/src/se2/vendor/igraph/CHANGELOG.md                                    | 2243 +++---
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Package CohortCharacteristics updated to version 1.0.1 with previous version 1.0.0 dated 2025-05-20

Title: Summarise and Visualise Characteristics of Patients in the OMOP CDM
Description: Summarise and visualise the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM).
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Mike Du [ctb] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Nuria Mercade-Besora [aut] , Marta Alcalde [aut]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between CohortCharacteristics versions 1.0.0 dated 2025-05-20 and 1.0.1 dated 2025-09-30

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Package surveytable updated to version 0.9.10 with previous version 0.9.9 dated 2025-08-25

Title: Streamlining Complex Survey Estimation and Reliability Assessment in R
Description: Short and understandable commands that generate tabulated, formatted, and rounded survey estimates. Mostly a wrapper for the 'survey' package (Lumley (2004) <doi:10.18637/jss.v009.i08> <https://CRAN.R-project.org/package=survey>) that identifies low-precision estimates using the National Center for Health Statistics (NCHS) presentation standards (Parker et al. (2017) <https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf>, Parker et al. (2023) <doi:10.15620/cdc:124368>).
Author: Alex Strashny [aut, cre]
Maintainer: Alex Strashny <alex.strashny@gmail.com>

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Package RBaM updated to version 1.1.1 with previous version 1.0.1 dated 2025-07-10

Title: Bayesian Modeling: Estimate a Computer Model and Make Uncertain Predictions
Description: An interface to the 'BaM' (Bayesian Modeling) engine, a 'Fortran'-based executable aimed at estimating a model with a Bayesian approach and using it for prediction, with a particular focus on uncertainty quantification. Classes are defined for the various building blocks of 'BaM' inference (model, data, error models, Markov Chain Monte Carlo (MCMC) samplers, predictions). The typical usage is as follows: (1) specify the model to be estimated; (2) specify the inference setting (dataset, parameters, error models...); (3) perform Bayesian-MCMC inference; (4) read, analyse and use MCMC samples; (5) perform prediction experiments. Technical details are available (in French) in Renard (2017) <https://hal.science/hal-02606929v1>. Examples of applications include Mansanarez et al. (2019) <doi:10.1029/2018WR023389>, Le Coz et al. (2021) <doi:10.1002/hyp.14169>, Perret et al. (2021) <doi:10.1029/2020WR027745>, Darienzo et al. (2021) <doi:10.1029/2020WR028607> and Pe [...truncated...]
Author: Benjamin Renard [aut, cre, cph] , INRAE [fnd], Ministere de la Transition Ecologique - SCHAPI [fnd]
Maintainer: Benjamin Renard <benjamin.renard@inrae.fr>

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Package NADA2 updated to version 2.0.1 with previous version 2.0.0 dated 2025-09-23

Title: Data Analysis for Censored Environmental Data
Description: Contains methods described by Dennis Helsel in his book "Statistics for Censored Environmental Data using Minitab and R" (2011) and courses and videos at <https://practicalstats.com>. This package incorporates functions of NADA and adds new functionality.
Author: Paul Julian [aut, cre], Dennis Helsel [aut, cph], Lopaka Lee [aut, cph]
Maintainer: Paul Julian <pauljulianphd@gmail.com>

Diff between NADA2 versions 2.0.0 dated 2025-09-23 and 2.0.1 dated 2025-09-30

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Package StepReg updated to version 1.6.0 with previous version 1.5.8 dated 2025-02-07

Title: Stepwise Regression Analysis
Description: Stepwise regression is a statistical technique used for model selection. This package streamlines stepwise regression analysis by supporting multiple regression types(linear, Cox, logistic, Poisson, Gamma, and negative binomial), incorporating popular selection strategies(forward, backward, bidirectional, and subset), and offering essential metrics. It enables users to apply multiple selection strategies and metrics in a single function call, visualize variable selection processes, and export results in various formats. StepReg offers a data-splitting option to address potential issues with invalid statistical inference and a randomized forward selection option to avoid overfitting. We validated StepReg's accuracy using public datasets within the SAS software environment. Additionally, StepReg features an interactive Shiny application to enhance usability and accessibility.
Author: Junhui Li [cre] , Junhui Li [aut], Kai Hu [aut], Xiaohuan Lu [aut], Sushmita N Nayak [ctb], Cesar Bautista Sotelo [ctb], Michael A Lodato [ctb], Wenxin Liu [aut], Lihua Julie Zhu [aut]
Maintainer: Junhui Li <junhui.li11@umassmed.edu>

Diff between StepReg versions 1.5.8 dated 2025-02-07 and 1.6.0 dated 2025-09-30

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New package torchMAUM with initial version 2025.7.30
Package: torchMAUM
Title: Multi-Class Area Under the Minimum in Torch
Version: 2025.7.30
Encoding: UTF-8
Description: Torch code for computing multi-class Area Under The Minimum, <https://www.jmlr.org/papers/v24/21-0751.html>, Generalization. Useful for optimizing Area under the curve.
License: LGPL-3
URL: https://github.com/OGuenoun/torchMAUM
BugReports: https://github.com/OGuenoun/torchMAUM/issues
Imports: torch, ggplot2, data.table
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-09-21 15:36:55 UTC; nou-z
Author: Omar Guenoun [aut, cre]
Maintainer: Omar Guenoun <omargue31@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 16:00:02 UTC

More information about torchMAUM at CRAN
Permanent link

Package systemfonts updated to version 1.3.0 with previous version 1.2.3 dated 2025-04-30

Title: System Native Font Finding
Description: Provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries on Windows, macOS and Linux for finding font files that can then be used further by e.g. graphic devices. The main use is intended to be from compiled code but 'systemfonts' also provides access from R.
Author: Thomas Lin Pedersen [aut, cre] , Jeroen Ooms [aut] , Devon Govett [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

Diff between systemfonts versions 1.2.3 dated 2025-04-30 and 1.3.0 dated 2025-09-30

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Package MiscMetabar updated to version 0.14.4 with previous version 0.14.3 dated 2025-06-21

Title: Miscellaneous Functions for Metabarcoding Analysis
Description: Facilitate the description, transformation, exploration, and reproducibility of metabarcoding analyses. 'MiscMetabar' is mainly built on top of the 'phyloseq', 'dada2' and 'targets' R packages. It helps to build reproducible and robust bioinformatics pipelines in R. 'MiscMetabar' makes ecological analysis of alpha and beta-diversity easier, more reproducible and more powerful by integrating a large number of tools. Important features are described in Taudière A. (2023) <doi:10.21105/joss.06038>.
Author: Adrien Taudiere [aut, cre, cph]
Maintainer: Adrien Taudiere <adrien.taudiere@zaclys.net>

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More information about MiscMetabar at CRAN
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Package backbone updated to version 3.0.1 with previous version 3.0.0 dated 2025-09-15

Title: Extracts the Backbone from Networks
Description: An implementation of methods for extracting a sparse unweighted network (i.e. a backbone) from an unweighted network (e.g., Hamann et al., 2016 <doi:10.1007/s13278-016-0332-2>), a weighted network (e.g., Serrano et al., 2009 <doi:10.1073/pnas.0808904106>), or a weighted projection (e.g., Neal et al., 2021 <doi:10.1038/s41598-021-03238-3>).
Author: Zachary Neal [aut, cre] , Rachel Domagalski [ctb], Bruce Sagan [ctb], Karl Godard [ctb]
Maintainer: Zachary Neal <zpneal@msu.edu>

Diff between backbone versions 3.0.0 dated 2025-09-15 and 3.0.1 dated 2025-09-30

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Package rodeo updated to version 0.9.2 with previous version 0.8.2 dated 2024-07-08

Title: A Code Generator for ODE-Based Models
Description: Provides an R6 class and several utility methods to facilitate the implementation of models based on ordinary differential equations. The heart of the package is a code generator that creates compiled 'Fortran' (or 'R') code which can be passed to a numerical solver. There is direct support for solvers contained in packages 'deSolve' and 'rootSolve'.
Author: David Kneis [cre, aut]
Maintainer: David Kneis <david.kneis@tu-dresden.de>

Diff between rodeo versions 0.8.2 dated 2024-07-08 and 0.9.2 dated 2025-09-30

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Package lmfor updated to version 1.7 with previous version 1.6 dated 2022-04-29

Title: Functions for Forest Biometrics
Description: Functions for different purposes related to forest biometrics, including illustrative graphics, numerical computation, modeling height-diameter relationships, prediction of tree volumes, modelling of diameter distributions and estimation off stand density using ITD. Several empirical datasets are also included.
Author: Lauri Mehtatalo [aut, cre], Kasper Kansanen [aut]
Maintainer: Lauri Mehtatalo <lauri.mehtatalo@luke.fi>

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Package booami updated to version 0.1.1 with previous version 0.1.0 dated 2025-09-04

Title: Component-Wise Gradient Boosting after Multiple Imputation
Description: Component-wise gradient boosting for analysis of multiply imputed datasets. Implements the algorithm Boosting after Multiple Imputation (MIBoost), which enforces uniform variable selection across imputations and provides utilities for pooling. Includes a cross-validation workflow that first splits the data into training and validation sets and then performs imputation on the training data, applying the learned imputation models to the validation data to avoid information leakage. Supports Gaussian and logistic loss. Methods relate to gradient boosting and multiple imputation as in Buehlmann and Hothorn (2007) <doi:10.1214/07-STS242>, Friedman (2001) <doi:10.1214/aos/1013203451>, and van Buuren (2018, ISBN:9781138588318) and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>; see also Kuchen (2025) <doi:10.48550/arXiv.2507.21807>.
Author: Robert Kuchen [aut, cre]
Maintainer: Robert Kuchen <rokuchen@uni-mainz.de>

Diff between booami versions 0.1.0 dated 2025-09-04 and 0.1.1 dated 2025-09-30

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Package tok updated to version 0.2.1 with previous version 0.2.0 dated 2025-08-27

Title: Fast Text Tokenization
Description: Interfaces with the 'Hugging Face' tokenizers library to provide implementations of today's most used tokenizers such as the 'Byte-Pair Encoding' algorithm <https://huggingface.co/docs/tokenizers/index>. It's extremely fast for both training new vocabularies and tokenizing texts.
Author: Daniel Falbel [aut, cre], Regouby Christophe [ctb], Posit [cph]
Maintainer: Daniel Falbel <daniel@posit.co>

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Package spatialising updated to version 0.6.2 with previous version 0.6.0 dated 2023-11-27

Title: Ising Model for Spatial Data
Description: Performs simulations of binary spatial raster data using the Ising model (Ising (1925) <doi:10.1007/BF02980577>; Onsager (1944) <doi:10.1103/PhysRev.65.117>). It allows to set a few parameters that represent internal and external pressures, and the number of simulations (Stepinski and Nowosad (2023) <doi:10.1098/rsos.231005>).
Author: Jakub Nowosad [aut, cre]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package sgs updated to version 0.3.9 with previous version 0.3.8 dated 2025-06-12

Title: Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control
Description: Implementation of Sparse-group SLOPE (SGS) (Feser and Evangelou (2023) <doi:10.48550/arXiv.2305.09467>) models. Linear and logistic regression models are supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported. In addition, a general Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) <doi:10.48550/arXiv.1804.02339>) implementation is provided. Group SLOPE (gSLOPE) (Brzyski et al. (2019) <doi:10.1080/01621459.2017.1411269>) and group-based OSCAR models (Feser and Evangelou (2024) <doi:10.48550/arXiv.2405.15357>) are also implemented. All models are available with strong screening rules (Feser and Evangelou (2024) <doi:10.48550/arXiv.2405.15357>) for computational speed-up.
Author: Fabio Feser [aut, cre]
Maintainer: Fabio Feser <ff120@ic.ac.uk>

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Package psbcSpeedUp updated to version 2.1.0 with previous version 2.0.7 dated 2024-07-01

Title: Penalized Semiparametric Bayesian Cox Models
Description: Algorithms to speed up the Bayesian Lasso Cox model (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and the Bayesian Lasso Cox with mandatory variables (Zucknick et al. Biometrical J, 2015 <doi:10.1002/bimj.201400160>).
Author: Zhi Zhao [aut, cre], Manuela Zucknick [aut], Maral Saadati [aut], Axel Benner [aut]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

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Package myClim updated to version 1.5.0 with previous version 1.4.0 dated 2025-02-21

Title: Microclimatic Data Processing
Description: Handling the microclimatic data in R. The 'myClim' workflow begins at the reading data primary from microclimatic dataloggers, but can be also reading of meteorological station data from files. Cleaning time step, time zone settings and metadata collecting is the next step of the work flow. With 'myClim' tools one can crop, join, downscale, and convert microclimatic data formats, sort them into localities, request descriptive characteristics and compute microclimatic variables. Handy plotting functions are provided with smart defaults.
Author: Matej Man [aut], Vojtech Kalcik [aut, cre], Martin Macek [aut], Josef Bruna [aut], Lucia Hederova [aut], Jan Wild [aut], Martin Kopecky [aut], Institute of Botany of the Czech Academy of Sciences [cph]
Maintainer: Vojtech Kalcik <Vojtech.Kalcik@ibot.cas.cz>

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Package dfr updated to version 0.1.6 with previous version 0.1.5 dated 2025-03-06

Title: Dual Feature Reduction for SGL
Description: Implementation of the Dual Feature Reduction (DFR) approach for the Sparse Group Lasso (SGL) and the Adaptive Sparse Group Lasso (aSGL) (Feser and Evangelou (2024) <doi:10.48550/arXiv.2405.17094>). The DFR approach is a feature reduction approach that applies strong screening to reduce the feature space before optimisation, leading to speed-up improvements for fitting SGL (Simon et al. (2013) <doi:10.1080/10618600.2012.681250>) and aSGL (Mendez-Civieta et al. (2020) <doi:10.1007/s11634-020-00413-8> and Poignard (2020) <doi:10.1007/s10463-018-0692-7>) models. DFR is implemented using the Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) <doi:10.48550/arXiv.1804.02339>) algorithm, with linear and logistic SGL models supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported.
Author: Fabio Feser [aut, cre]
Maintainer: Fabio Feser <ff120@ic.ac.uk>

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Package spBFA updated to version 1.4.0 with previous version 1.3 dated 2023-03-21

Title: Spatial Bayesian Factor Analysis
Description: Implements a spatial Bayesian non-parametric factor analysis model with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). Spatial correlation is introduced in the columns of the factor loadings matrix using a Bayesian non-parametric prior, the probit stick-breaking process. Areal spatial data is modeled using a conditional autoregressive (CAR) prior and point-referenced spatial data is treated using a Gaussian process. The response variable can be modeled as Gaussian, probit, Tobit, or Binomial (using Polya-Gamma augmentation). Temporal correlation is introduced for the latent factors through a hierarchical structure and can be specified as exponential or first-order autoregressive. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in "Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces", by Berchuck et al (2019), <doi:10.1214/20-BA1253> in Bayesian Analysis.
Author: Samuel I. Berchuck [aut, cre]
Maintainer: Samuel I. Berchuck <sib2@duke.edu>

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Package manydata updated to version 1.1.3 with previous version 1.0.3 dated 2025-06-18

Title: Many Global Governance Datacubes
Description: This is the core package offering a portal to the many packages universe. It includes functions to help researchers access, work across, and maintain ensembles of datasets on global governance called datacubes.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [aut, ctb] , Bernhard Bieri [ctb] , Esther Peev [ctb] , Jael Tan [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package kstMatrix updated to version 1.3-0 with previous version 1.2-0 dated 2025-04-02

Title: Basic Functions in Knowledge Space Theory Using Matrix Representation
Description: Knowledge space theory by Doignon and Falmagne (1999) <doi:10.1007/978-3-642-58625-5> is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The 'kstMatrix' package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces. Opposed to the 'kst' package, 'kstMatrix' uses matrix representations for knowledge structures. Furthermore, 'kstMatrix' contains several knowledge spaces developed by the research group around Cornelia Dowling through querying experts.
Author: Cord Hockemeyer [aut, cre], Wai Wong [ctb]
Maintainer: Cord Hockemeyer <cord.hockemeyer@uni-graz.at>

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Package surveydown updated to version 0.13.3 with previous version 0.13.0 dated 2025-08-20

Title: Markdown-Based Programmable Surveys Using 'Quarto' and 'shiny'
Description: Generate programmable surveys using markdown and R code chunks. Surveys are composed of two files: a survey.qmd 'Quarto' file defining the survey content (pages, questions, etc), and an app.R file defining a 'shiny' app with global settings (libraries, database configuration, etc.) and server configuration options (e.g., conditional skipping / display, etc.). Survey data collected from respondents is stored in a 'PostgreSQL' database. Features include controls for conditional skip logic (skip to a page based on an answer to a question), conditional display logic (display a question based on an answer to a question), a customizable progress bar, and a wide variety of question types, including multiple choice (single choice and multiple choices), select, text, numeric, multiple choice buttons, text area, and dates. Because the surveys render into a 'shiny' app, designers can also leverage the reactive capabilities of 'shiny' to create dynamic and interactive surveys.
Author: John Paul Helveston [aut, cre, cph] , Pingfan Hu [aut, cph] , Bogdan Bunea [aut, cph] , Stefan Munnes [ctb]
Maintainer: John Paul Helveston <john.helveston@gmail.com>

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Package randomForestSRC updated to version 3.4.2 with previous version 3.4.1 dated 2025-06-07

Title: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
Description: Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Minimal depth variable importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.
Author: Hemant Ishwaran [aut], Udaya B. Kogalur [aut, cre]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

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Package ivo.table updated to version 0.7.0 with previous version 0.6 dated 2025-01-15

Title: Nicely Formatted Contingency Tables and Frequency Tables
Description: Nicely formatted frequency tables and contingency tables (1-way, 2-way, 3-way and 4-way tables), that can easily be exported to HTML or 'Office' documents. Designed to work with pipes.
Author: Mans Thulin [aut, cre], Kajsa Grind [aut], Stefan Furne [aut]
Maintainer: Mans Thulin <mans@statistikkonsult.com>

Diff between ivo.table versions 0.6 dated 2025-01-15 and 0.7.0 dated 2025-09-30

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Package stRoke updated to version 25.9.2 with previous version 25.9.1 dated 2025-09-02

Title: Clinical Stroke Research
Description: A collection of tools for clinical trial data management and analysis in research and teaching. The package is mainly collected for personal use, but any use beyond that is encouraged. This package has migrated functions from 'agdamsbo/daDoctoR', and new functions has been added. Version follows months and year. See NEWS/Changelog for release notes. This package includes sampled data from the TALOS trial (Kraglund et al (2018) <doi:10.1161/STROKEAHA.117.020067>). The win_prob() function is based on work by Zou et al (2022) <doi:10.1161/STROKEAHA.121.037744>. The age_calc() function is based on work by Becker (2020) <doi:10.18637/jss.v093.i02>.
Author: Andreas Gammelgaard Damsbo [aut, cre]
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@clin.au.dk>

Diff between stRoke versions 25.9.1 dated 2025-09-02 and 25.9.2 dated 2025-09-30

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Package RcppCWB updated to version 0.6.10 with previous version 0.6.9 dated 2025-09-27

Title: 'Rcpp' Bindings for the 'Corpus Workbench' ('CWB')
Description: 'Rcpp' Bindings for the C code of the 'Corpus Workbench' ('CWB'), an indexing and query engine to efficiently analyze large corpora (<https://cwb.sourceforge.io>). 'RcppCWB' is licensed under the GNU GPL-3, in line with the GPL-3 license of the 'CWB' (<https://www.r-project.org/Licenses/GPL-3>). The 'CWB' relies on 'pcre2' (BSD license, see <https://github.com/PCRE2Project/pcre2/blob/master/LICENCE.md>) and 'GLib' (LGPL license, see <https://www.gnu.org/licenses/lgpl-3.0.en.html>). See the file LICENSE.note for further information. The package includes modified code of the 'rcqp' package (GPL-2, see <https://cran.r-project.org/package=rcqp>). The original work of the authors of the 'rcqp' package is acknowledged with great respect, and they are listed as authors of this package. To achieve cross-platform portability (including Windows), using 'Rcpp' for wrapper code is the approach used by 'RcppCWB'.
Author: Andreas Blaette [aut, cre], Bernard Desgraupes [aut], Sylvain Loiseau [aut], Oliver Christ [ctb], Bruno Maximilian Schulze [ctb], Stephanie Evert [ctb], Arne Fitschen [ctb], Jeroen Ooms [ctb], Marius Bertram [ctb], Tomas Kalibera [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

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Package openssl updated to version 2.3.4 with previous version 2.3.3 dated 2025-05-26

Title: Toolkit for Encryption, Signatures and Certificates Based on OpenSSL
Description: Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers. Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric (public key) encryption or EC for Diffie Hellman. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and 'bignum' math methods for manually performing crypto calculations on large multibyte integers.
Author: Jeroen Ooms [aut, cre] , Oliver Keyes [ctb]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between openssl versions 2.3.3 dated 2025-05-26 and 2.3.4 dated 2025-09-30

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 12 files changed, 83 insertions(+), 73 deletions(-)

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New package writeAlizer with initial version 1.6.4
Package: writeAlizer
Title: Generate Predicted Writing Quality Scores
Version: 1.6.4
Date: 2025-09-23
Description: Imports variables from 'ReaderBench' (Dascalu et al., 2018)<doi:10.1007/978-3-319-66610-5_48>, 'Coh-Metrix' (McNamara et al., 2014)<doi:10.1017/CBO9780511894664>, and/or 'GAMET' (Crossley et al., 2019) <doi:10.17239/jowr-2019.11.02.01> output files; downloads predictive scoring models described in Mercer & Cannon (2022)<doi:10.31244/jero.2022.01.03> and Mercer et al.(2021)<doi:10.1177/0829573520987753>; and generates predicted writing quality and curriculum-based measurement (McMaster & Espin, 2007)<doi:10.1177/00224669070410020301> scores.
License: GPL-3
URL: https://github.com/shmercer/writeAlizer/
BugReports: https://github.com/shmercer/writeAlizer/issues
Depends: R (>= 2.10)
Imports: caret, digest, dplyr, glue, magrittr, stats, tidyselect, utils
Suggests: caretEnsemble, Cubist, earth, gbm, glmnet, kernlab, pls, randomForest, testthat (>= 3.1.0), withr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-09-23 18:59:25 UTC; shmer
Author: Sterett H. Mercer [aut, cre]
Maintainer: Sterett H. Mercer <sterett.mercer@ubc.ca>
Repository: CRAN
Date/Publication: 2025-09-30 08:40:02 UTC

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New package TwoDcDAPSA with initial version 0.1.0
Package: TwoDcDAPSA
Title: Calculate TwoDcDAPSA: PROs-Joint Contrast (PJC) Score and Quartiles
Version: 0.1.0
Description: Provides a calculator for the two-dimensional clinical Disease Activity index for Psoriatic Arthritis (TwoDcDAPSA), a principal component-derived measure that complements the conventional clinical DAPSA score. The TwoDcDAPSA captures residual variation in patient-reported outcomes (pain and patient global assessment) and joint counts (swollen and tender) after adjusting for standardized cDAPSA using natural spline coefficients derived from published models. Residuals are standardized and combined with fixed principal component loadings to yield a continuous PROs-Joint Contrast (PJC) score and quartile groupings. The package applies pre-specified coefficients and loadings to new datasets but does not estimate spline models or principal components itself.
License: MIT + file LICENSE
Depends: R (>= 3.6)
Imports: dplyr, splines, rlang
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-09-23 19:26:21 UTC; nmeng2
Author: Ning Meng [aut, cre], Ji Soo Kim [aut], Ana-Maria Orbai [aut], Scott L. Zeger [aut]
Maintainer: Ning Meng <nmeng2@jh.edu>
Repository: CRAN
Date/Publication: 2025-09-30 08:40:08 UTC

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New package twbparser with initial version 0.2.3
Package: twbparser
Title: Parse 'Tableau' Workbooks into Functional Data
Version: 0.2.3
Description: High-performance parsing of 'Tableau' workbook files into tidy data frames and dependency graphs for other visualization tools like R 'Shiny' or 'Power BI' replication.
License: MIT + file LICENSE
URL: https://prigasg.github.io/twbparser/, https://github.com/PrigasG/twbparser
BugReports: https://github.com/PrigasG/twbparser/issues
Depends: R (>= 4.2.0)
Imports: dplyr, igraph, purrr, R6, rlang, stringr, tibble, tidyr, withr, xml2
Suggests: cli, covr, ggraph, knitr, lintr, magrittr, optparse, rmarkdown, spelling, styler, testthat (>= 3.0.0), tidygraph, vctrs, zip
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-09-23 16:26:11 UTC; garthur
Author: George Arthur [aut, cre]
Maintainer: George Arthur <prigasgenthian48@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 08:30:02 UTC

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New package tidyusmacro with initial version 0.1.0
Package: tidyusmacro
Title: Downloading and Cleaning U.S. Macroeconomic Data
Version: 0.1.0
Description: Utilities to retrieve and tidy U.S. macroeconomic data series from public government data providers. Functions streamline access to series from the Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED), the Bureau of Labor Statistics flat files, and the Bureau of Economic Analysis National Income and Product Accounts tables, then return consistent, tidy data frames ready for modeling and graphics. The package includes helpers for date alignment, log-linear projections, and common macro diagnostics, along with convenience plot builders for quick publication-quality charts.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
Imports: dplyr, ggplot2, magrittr, purrr, readr, rlang, stringi, tidyr
NeedsCompilation: no
Packaged: 2025-09-24 03:37:40 UTC; mtkonczal
Author: Mike Konczal [aut, cre]
Maintainer: Mike Konczal <konczal@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 08:50:02 UTC

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New package streamsampler with initial version 0.1.0
Package: streamsampler
Title: Characterize and Subsample Stream Data
Version: 0.1.0
Description: Characterize daily stream discharge and water quality data and subsample water quality data. Provide dates, discharge, and water quality measurements and 'streamsampler' can find gaps, get summary statistics, and subsample according to common stream sampling protocols. Stream sampling protocols are described in Lee et al. (2016) <doi:10.1016/j.jhydrol.2016.08.059> and Lee et al. (2019) <doi:10.3133/sir20195084>.
License: CC0
URL: https://github.com/Kyle-Hurley/streamsampler
BugReports: https://github.com/Kyle-Hurley/streamsampler/issues
Encoding: UTF-8
Suggests: dataRetrieval (>= 2.7.16), knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1)
LazyData: true
Imports: slider (>= 0.3.1), stats
VignetteBuilder: knitr
Copyright: This software is in the public domain because it contains materials that originally came from the United States Geological Survey, an agency of the United States Department of Interior. For more information, see the official USGS copyright policy at https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits
NeedsCompilation: no
Packaged: 2025-09-23 12:25:18 UTC; kphur
Author: Kyle Hurley [aut, cre, cph] , Jeff Chanat [aut]
Maintainer: Kyle Hurley <kp.hurley87@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 08:30:09 UTC

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New package splineplot with initial version 0.1.1
Package: splineplot
Title: Visualization of Spline Effects in GAM and GLM Models
Version: 0.1.1
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>
Description: Creates 'ggplot2'-based visualizations of smooth effects from GAM (Generalized Additive Models) fitted with 'mgcv' and spline effects from GLM (Generalized Linear Models). Supports interaction terms and provides hazard ratio plots with histograms for survival analysis. Wood (2017, ISBN:9781498728331) provides comprehensive methodology for generalized additive models.
License: Apache License 2.0
Encoding: UTF-8
Imports: ggplot2 (>= 3.0.0), stats
Suggests: mgcv, survival, splines, testthat (>= 3.0.0), knitr, rmarkdown, covr, pkgdown
VignetteBuilder: knitr
URL: https://github.com/jinseob2kim/splineplot, https://jinseob2kim.github.io/splineplot/
BugReports: https://github.com/jinseob2kim/splineplot/issues
NeedsCompilation: no
Packaged: 2025-09-23 15:09:22 UTC; js
Author: Jinseob Kim [aut, cre] , Zarathu [cph, fnd]
Repository: CRAN
Date/Publication: 2025-09-30 08:30:14 UTC

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New package SFHNV with initial version 0.1.0
Package: SFHNV
Title: Structural Forest for the Heterogeneous Newsvendor Model
Version: 0.1.0
Description: Implements the structural forest methodology for the heterogeneous newsvendor model. The package provides tools to prepare data, fit honest newsvendor trees and forests, and obtain point and distributional predictions for demand decisions under uncertainty.
URL: https://github.com/MurphyLiCN/SFHNV
License: MIT + file LICENSE
Depends: R (>= 3.6)
Imports: stats
Suggests: future.apply, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-09-22 01:56:31 UTC; murphy
Author: Mengfei Li [aut, cre]
Maintainer: Mengfei Li <murphy.li.cn@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 08:50:14 UTC

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Package satin updated to version 1.2.0 with previous version 1.1.0 dated 2022-09-22

Title: Visualisation and Analysis of Ocean Data Derived from Satellites
Description: With 'satin' functions, visualisation, data extraction and further analysis like producing climatologies from several images, and anomalies of satellite derived ocean data can be easily done. Reading functions can import a user defined geographical extent of data stored in netCDF files. Currently supported ocean data sources include NASA's Oceancolor web page <https://oceancolor.gsfc.nasa.gov/>, sensors VIIRS-SNPP; MODIS-Terra; MODIS-Aqua; and SeaWiFS. Available variables from this source includes chlorophyll concentration, sea surface temperature (SST), and several others. Data sources specific for SST that can be imported too includes Pathfinder AVHRR <https://www.ncei.noaa.gov/products/avhrr-pathfinder-sst> and GHRSST <https://www.ghrsst.org/>. In addition, ocean productivity data produced by Oregon State University can also be handled previous conversion from HDF4 to HDF5 format. Many other ocean variables can be processed by importing netCDF data files from [...truncated...]
Author: Hector Villalobos [aut, cre] , Eduardo Gonzalez-Rodriguez [aut]
Maintainer: Hector Villalobos <hvillalo@ipn.mx>

Diff between satin versions 1.1.0 dated 2022-09-22 and 1.2.0 dated 2025-09-30

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Package rpaleoclim updated to version 1.1.0 with previous version 1.0.1 dated 2023-08-09

Title: Download Paleoclimate Data from 'PaleoClim'
Description: 'PaleoClim' <http://www.paleoclim.org> (Brown et al. 2019, <doi:10.1038/sdata.2018.254>) is a set of free, high resolution paleoclimate surfaces covering the whole globe. It includes data on surface temperature, precipitation and the standard bioclimatic variables commonly used in ecological modelling, derived from the 'HadCM3' general circulation model and downscaled to a spatial resolution of up to 2.5 minutes. Simulations are available for key time periods from the Late Holocene to mid-Pliocene. Data on current and Last Glacial Maximum climate is derived from 'CHELSA' (Karger et al. 2017, <doi:10.1038/sdata.2017.122>) and reprocessed by 'PaleoClim' to match their format; it is available at up to 30 seconds resolution. This package provides a simple interface for downloading 'PaleoClim' data in R, with support for caching and filtering retrieved data by period, resolution, and geographic extent.
Author: Joe Roe [aut, cre, cph]
Maintainer: Joe Roe <joe@joeroe.io>

Diff between rpaleoclim versions 1.0.1 dated 2023-08-09 and 1.1.0 dated 2025-09-30

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Package rmarchingcubes updated to version 0.1.4 with previous version 0.1.2 dated 2021-06-16

Title: Calculate 3D Contour Meshes Using the Marching Cubes Algorithm
Description: A port of the C++ routine for applying the marching cubes algorithm written by Thomas Lewiner et al. (2012) <doi:10.1080/10867651.2003.10487582> into an R package. The package supplies the contour3d() function, which takes a 3-dimensional array of voxel data and calculates the vertices, vertex normals, and faces for a 3d mesh representing the contour(s) at a given level.
Author: S. H. Wilks [aut, cre], Thomas Lewiner [aut]
Maintainer: S. H. Wilks <sam.wilks@unimelb.edu.au>

Diff between rmarchingcubes versions 0.1.2 dated 2021-06-16 and 0.1.4 dated 2025-09-30

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 17 files changed, 488 insertions(+), 257 deletions(-)

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Package pollen updated to version 0.83.0 with previous version 0.82.0 dated 2021-12-03

Title: Analysis of Aerobiological Data
Description: Supports analysis of aerobiological data. Available features include determination of pollen season limits, replacement of outliers (Kasprzyk and Walanus (2014) <doi:10.1007/s10453-014-9332-8>), calculation of growing degree days (Baskerville and Emin (1969) <doi:10.2307/1933912>), and determination of the base temperature for growing degree days (Yang et al. (1995) <doi:10.1016/0168-1923(94)02185-M).
Author: Jakub Nowosad [aut, cre]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between pollen versions 0.82.0 dated 2021-12-03 and 0.83.0 dated 2025-09-30

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New package powergrid with initial version 0.5.0
Package: powergrid
Title: Power Analysis Across a Grid of Assumptions
Version: 0.5.0
Description: Evaluate a function across a grid of parameters. The function may be evaluated once, or many times for simulation. Parallel computing is facilitated. Utilities aim at performing analyses of power and sample size, allowing for easy search of minimum n (or min/max of any other parameter) to achieve a desired minimal level of power (or maximum of any other objective). Plotting functions are included that present the dependency of n and power in relation to further assumptions.
License: GPL-3
Encoding: UTF-8
Suggests: future.apply (>= 1.11.2), future (>= 1.33.2), knitr, rmarkdown, testthat (>= 3.0.0)
Imports: stats, methods
VignetteBuilder: knitr
URL: https://github.com/SwissClinicalTrialOrganisation/powergrid
BugReports: https://github.com/SwissClinicalTrialOrganisation/powergrid/issues
NeedsCompilation: no
Packaged: 2025-09-23 09:57:22 UTC; gilles
Author: Gilles Dutilh [aut, cre] , Richard Charles Allen [aut]
Maintainer: Gilles Dutilh <info@gillesdutilh.com>
Repository: CRAN
Date/Publication: 2025-09-30 08:20:02 UTC

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Package OSMscale updated to version 0.5.23 with previous version 0.5.22 dated 2025-07-27

Title: Add a Scale Bar to 'OpenStreetMap' Plots
Description: Functionality to handle and project lat-long coordinates, easily download background maps and add a correct scale bar to 'OpenStreetMap' plots in any map projection.
Author: Berry Boessenkool [aut, cre]
Maintainer: Berry Boessenkool <berry-b@gmx.de>

Diff between OSMscale versions 0.5.22 dated 2025-07-27 and 0.5.23 dated 2025-09-30

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 10 files changed, 54 insertions(+), 27 deletions(-)

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New package houba with initial version 0.1.0
Package: houba
Title: Manipulation of (Large) Memory-Mapped Objects (Vectors, Matrices and Arrays)
Version: 0.1.0
Date: 2025-09-17
Maintainer: Herve Perdry <herve.perdry@universite-paris-saclay.fr>
Description: Manipulate data through memory-mapped files, as vectors, matrices or arrays. Basic arithmetic functions are implemented, but currently no matrix arithmetic. Can write and read descriptor files for compatibility with the 'bigmemory' package.
License: CeCILL-2
Encoding: UTF-8
Depends: methods
Imports: Rcpp (>= 1.0.11)
Suggests: knitr, bigmemory
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2025-09-23 12:44:45 UTC; rv
Author: Herve Perdry [aut, cre], Juliette Meyniel [aut]
Repository: CRAN
Date/Publication: 2025-09-30 08:30:20 UTC

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Package GABB updated to version 0.3.10 with previous version 0.3.9 dated 2025-05-14

Title: Facilitation of Data Preparation and Plotting Procedures for RDA and PCA Analyses
Description: Help to the occasional R user for synthesis and enhanced graphical visualization of redundancy analysis (RDA) and principal component analysis (PCA) methods and objects. Inputs are : data frame, RDA (package 'vegan') and PCA (package 'FactoMineR') objects. Outputs are : synthesized results of RDA, displayed in console and saved in tables ; displayed and saved objects of PCA graphic visualization of individuals and variables projections with multiple graphic parameters.
Author: Gregoire Bianchetti [aut, cre]
Maintainer: Gregoire Bianchetti <auguste.blam@gmail.com>

Diff between GABB versions 0.3.9 dated 2025-05-14 and 0.3.10 dated 2025-09-30

 DESCRIPTION          |    8 ++++----
 MD5                  |    4 ++--
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 3 files changed, 16 insertions(+), 9 deletions(-)

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New package blox with initial version 0.0.1
Package: blox
Title: Block Diagonal Matrix Approximation
Version: 0.0.1
Maintainer: Jan O. Bauer <j.bauer@vu.nl>
Description: Finds the best block diagonal matrix approximation of a symmetric matrix. This can be exploited for divisive hierarchical clustering using singular vectors, named HC-SVD. The method is described in Bauer (202Xa) <doi:10.48550/arXiv.2308.06820>.
License: GPL (>= 2)
Imports: matrixStats, Rcpp, RcppArmadillo
Encoding: UTF-8
Suggests: corrplot, knitr, psych, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2025-09-24 09:00:39 UTC; jan
Author: Jan O. Bauer [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-30 09:00:13 UTC

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New package ZIDW with initial version 0.1.0
Package: ZIDW
Version: 0.1.0
Date: 2025-09-22
Title: Zero-Inflated Discrete Weibull Models
Depends: R (>= 4.1.0)
Imports: DWreg, actuar, maxLik, COUNT, gtools, matrixcalc, DiscreteWeibull, dplyr, ggplot2, purrr, tibble
URL: https://github.com/dsy109/ZIDW
Description: Parameter estimation for zero-inflated discrete Weibull (ZIDW) regression models, the univariate setting, distribution functions, functions to generate randomized quantile residuals a pseudo R2, and plotting of rootograms. For more details, see Kalktawi (2017) <https://bura.brunel.ac.uk/handle/2438/14476>, Taconeli and Rodrigues de Lara (2022) <doi:10.1080/00949655.2021.2005597>, and Yeh and Young (2025) <doi:10.1080/03610918.2025.2464076>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2025-09-22 16:02:02 UTC; derekyoung
Author: Peng Yeh [aut], Derek S. Young [aut, cre]
Maintainer: Derek S. Young <derek.young@uky.edu>
Repository: CRAN
Date/Publication: 2025-09-30 07:20:22 UTC

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Package rstanarm updated to version 2.32.2 with previous version 2.32.1 dated 2024-01-18

Title: Bayesian Applied Regression Modeling via Stan
Description: Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
Author: Jonah Gabry [aut], Imad Ali [ctb], Sam Brilleman [ctb], Jacqueline Buros Novik [ctb] , AstraZeneca [ctb] , Trustees of Columbia University [cph], Simon Wood [cph] , R Core Deveopment Team [cph] , Douglas Bates [cph] , Martin Maechler [cph] , Ben Bolk [...truncated...]
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

Diff between rstanarm versions 2.32.1 dated 2024-01-18 and 2.32.2 dated 2025-09-30

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New package rcldf with initial version 1.5.1
Package: rcldf
Title: Read Linguistic Data in the Cross Linguistic Data Format (CLDF)
Version: 1.5.1
Maintainer: Simon J. Greenhill <simon@simon.net.nz>
Description: Cross-Linguistic Data Format (CLDF) is a framework for storing cross-linguistic data, ensuring compatibility and ease of data exchange between different linguistic datasets see Forkel et al. (2018) <doi:10.1038/sdata.2018.205>. The 'rcldf' package is designed to facilitate the manipulation and analysis of these datasets by simplifying the loading, querying, and visualisation of CLDF datasets making it easier to conduct comparative linguistic analyses, manage language data, and apply statistical methods directly within R.
License: Apache License (>= 2.0)
Encoding: UTF-8
Imports: archive, bib2df (>= 1.1.1), csvwr, digest, dplyr, jsonlite, logger, magrittr, purrr, readr, remotes, rlang, tools, urltools, utils
Suggests: ggplot2, patchwork, testthat, mockthat, spelling, covr, knitr, rmarkdown, qpdf
URL: https://github.com/SimonGreenhill/rcldf
BugReports: https://github.com/SimonGreenhill/rcldf/issues
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-22 08:05:55 UTC; simon
Author: Simon J. Greenhill [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-30 07:20:02 UTC

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New package radviz3d with initial version 2.3.0
Package: radviz3d
Title: 3D Radial Visualization
Version: 2.3.0
Description: Creating 3D radial visualizations of multivariate data. The package extends traditional radial coordinate visualization (RadViz) techniques to three-dimensional space, enabling enhanced exploration and analysis of high-dimensional datasets through interactive 3D plots. Zhu, Dai & Maitra (2022) <doi:10.1080/10618600.2021.2020129>.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: rgl (>= 0.100.19)
Suggests: MixSim, gtools
Author: Yifan Zhu [cre, aut], Fan Dai [aut], Ranjan Maitra [aut], Niraj Kunwar [aut], Gani Agadilov [aut]
Maintainer: Yifan Zhu <yifanzhu@iastate.edu>
NeedsCompilation: no
Packaged: 2025-09-23 07:12:54 UTC; yifanzhu
Repository: CRAN
Date/Publication: 2025-09-30 07:50:02 UTC

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New package OmopConstructor with initial version 0.1.0
Package: OmopConstructor
Title: Build Tables in the OMOP Common Data Model
Version: 0.1.0
Description: Provides functionality to construct standardised tables from health care data formatted according to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. The package includes tools to build key tables such as observation period and drug era, among others.
License: Apache License (>= 2)
Encoding: UTF-8
Imports: cli, clock, dplyr, glue, omopgenerics, PatientProfiles, purrr, rlang, tidyr
Depends: R (>= 4.1)
Suggests: bookdown, CDMConnector, duckdb, ggplot2, gt, knitr, odbc, omock, OmopSketch, rmarkdown, RPostgres, stringr, testthat (>= 3.0.0), visOmopResults
URL: https://ohdsi.github.io/OmopConstructor/
BugReports: https://github.com/ohdsi/OmopConstructor/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-22 19:23:49 UTC; martics
Author: Marti Catala [aut, cre] , Elin Rowlands [ctb] , Cecilia Campanile [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>
Repository: CRAN
Date/Publication: 2025-09-30 07:20:28 UTC

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New package nonParQuantileCausality with initial version 0.1.0
Package: nonParQuantileCausality
Title: Nonparametric Causality in Quantiles Test
Version: 0.1.0
Author: Mehmet Balcilar [aut, cre]
Maintainer: Mehmet Balcilar <mehmet@mbalcilar.net>
Description: Implements the nonparametric causality-in-quantiles test (in mean or variance), returning a test object with an S3 plot() method. The current implementation uses one lag of each series (first-order Granger causality setup). Methodology is based on Balcilar, Gupta, and Pierdzioch (2016a) <doi:10.1016/j.resourpol.2016.04.004> and Balcilar et al. (2016) <doi:10.1007/s11079-016-9388-x>.
License: MIT + file LICENSE
URL: https://www.mbalcilar.net, https://github.com/mbalcilar/nonParQuantileCausality
Encoding: UTF-8
LazyData: true
LazyDataCompression: bzip2
Depends: R (>= 3.6)
Imports: stats, ggplot2, quantreg, KernSmooth
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-22 20:25:08 UTC; mbalcilar
Repository: CRAN
Date/Publication: 2025-09-30 07:20:08 UTC

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New package myownrobs with initial version 0.1.0
Package: myownrobs
Title: AI Coding Agent for 'RStudio'
Version: 0.1.0
Maintainer: Juan Cruz Rodriguez <jcrodriguez@unc.edu.ar>
Description: Provides an 'RStudio' extension with a chat interface for an AI coding agent to help users with R programming tasks.
License: MIT + file LICENSE
URL: https://myownrobs.github.io/myownrobs/, https://github.com/MyOwnRobs/myownrobs
BugReports: https://github.com/MyOwnRobs/myownrobs/issues
Encoding: UTF-8
Imports: fs, gargle, glue, httr2, jsonlite, mirai, rstudio.prefs, rstudioapi, shiny, tools, uuid, yaml
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-09-22 23:25:27 UTC; jcrodriguez
Author: Juan Cruz Rodriguez [aut, cre]
Repository: CRAN
Date/Publication: 2025-09-30 07:30:02 UTC

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New package mammalcol with initial version 0.2.9
Package: mammalcol
Title: Access to the List of Mammal Species of Colombia
Version: 0.2.9
Date: 2025-09-22
Maintainer: Diego J. Lizcano <dj.lizcano@gmail.com>
Description: The goal of 'mammalcol' is to provide easy access to a meticulously structured dataset of Colombian mammal species in R. The 2025 update includes comprehensive, detailed species accounts, and distribution information.
License: MIT + file LICENSE
URL: https://github.com/dlizcano/mammalcol, https://dlizcano.github.io/mammalcol/
BugReports: https://github.com/dlizcano/mammalcol/issues
Depends: R (>= 3.5.0)
Imports: ggplot2, magrittr, sf, geodata,
Suggests: dplyr, finch, knitr, readr, readxl, rmarkdown, stringr, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-22 16:51:35 UTC; usuario
Author: Diego J. Lizcano [aut, cre] , Cristian A. Cruz-Rodriguez [ctb, aut] , Andres F. Suarez-Castro [ctb, aut] , Baltazar Gonzalez [ctb, aut] , Alejandra Bonilla-Sanchez [ctb] , Camilo A. Calderon-Acevedo [ctb]
Repository: CRAN
Date/Publication: 2025-09-30 07:20:13 UTC

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New package foodwebr with initial version 1.0.0
Package: foodwebr
Title: Visualise Function Dependencies
Version: 1.0.0
Description: Easily create graphs of the inter-relationships between functions in an environment.
License: MIT + file LICENSE
URL: https://lewinfox.com/foodwebr/
BugReports: https://github.com/lewinfox/foodwebr/issues
Imports: cli, crayon, codetools, DiagrammeR, glue, rlang, stringr, tidygraph
Suggests: testthat
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2025-09-23 04:44:26 UTC; lewin
Author: Lewin Appleton-Fox [aut, cre]
Maintainer: Lewin Appleton-Fox <lewin.a.f@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 07:30:07 UTC

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New package DyadRatios with initial version 1.2
Package: DyadRatios
Title: Dyad Ratios Algorithm
Version: 1.2
Date: 2025-09-22
Description: Estimates the Dyad Ratios Algorithm for pooling and smoothing poll estimates. The Dyad Ratios Algorithm smooths both forward and backward in time over polling results allowing differences in both question type and polling house. The result is an estimate of a single latent variable that describes the systematic trend over time in the (noisy) polling results. See James A. Stimson (2018) <doi:10.1177/0759106318761614> and the package's vignette for more details.
Depends: R (>= 3.5.0)
Imports: ggplot2, lubridate, stats
License: GPL (>= 2)
Encoding: UTF-8
Suggests: dplyr, rio, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-09-22 19:06:45 UTC; david
Author: Dave Armstrong [cre], James Stimson [aut]
Maintainer: Dave Armstrong <davearmstrong.ps@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-30 07:20:33 UTC

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New package docorator with initial version 0.5.0
Package: docorator
Title: Docorate (Decorate + Output) Displays
Version: 0.5.0
Description: A framework for creating production outputs. Users can frame a table, listing, or figure with headers and footers and save to an output file. Stores an intermediate 'docorator' object for reproducibility and rendering to multiple output types.
License: Apache License 2.0
Encoding: UTF-8
Imports: gt (>= 0.11.0), rmarkdown, rlang, cli, dplyr, rstudioapi, purrr, stringr, tidyr, lifecycle, png, knitr, withr, quarto
Suggests: rprojroot, testthat (>= 3.0.0), tfrmt, pdftools, ggplot2
VignetteBuilder: knitr
URL: https://GSK-Biostatistics.github.io/docorator/, https://github.com/GSK-Biostatistics/docorator
BugReports: https://github.com/GSK-Biostatistics/docorator/issues
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2025-09-22 15:38:15 UTC; bkrouse
Author: Becca Krouse [aut, cre], Shannon Haughton [aut], Seongbin Hong [aut], DragoČ™ Moldovan-Gruenfeld [aut], GlaxoSmithKline Research & Development Limited [cph, fnd]
Maintainer: Becca Krouse <becca.z.krouse@gsk.com>
Repository: CRAN
Date/Publication: 2025-09-30 07:10:02 UTC

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New package coglyphr with initial version 1.0.4
Package: coglyphr
Title: Compute Glyph Centers of Gravity from Image Data
Version: 1.0.4
Description: Computes the center of gravity (COG) of character-like binary images using three different methods. This package provides functions for estimating stroke-based, contour-based, and potential energy-based COG. It is useful for analyzing glyph structure in areas such as visual cognition research and font development. The contour-based method was originally proposed by Kotani et al. (2004) <https://ipsj.ixsq.nii.ac.jp/records/36793> and Kotani (2011) <https://shonan-it.repo.nii.ac.jp/records/2000243>, while the potential energy-based method was introduced by Kotani et al. (2006) <doi:10.11371/iieej.35.296>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/mutopsy/coglyphr, https://mutopsy.github.io/coglyphr/
BugReports: https://github.com/mutopsy/coglyphr/issues
Depends: R (>= 4.4.0)
Imports: imager, dplyr, sp
LazyData: true
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-09-23 08:57:31 UTC; owner
Author: Hiroyuki Muto [aut, cre]
Maintainer: Hiroyuki Muto <mutopsy@omu.ac.jp>
Repository: CRAN
Date/Publication: 2025-09-30 08:00:11 UTC

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New package captain with initial version 1.1.1
Package: captain
Title: Running 'git' Pre-Commit Hooks
Version: 1.1.1
Description: Git hook scripts are useful for identifying simple issues before submission to code review. 'captain' (hook) is an R package to manage and run git pre-commit hooks.
License: MIT + file LICENSE
URL: https://github.com/alexym1/captain, https://alexym1.github.io/captain/
BugReports: https://github.com/alexym1/captain/issues
Depends: R (>= 4.1.0)
Imports: cli, fs, yaml
Suggests: devtools, covr, knitr, styler, testthat, withr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-09-22 20:22:11 UTC; Admin
Author: Alex Yahiaoui Martinez [aut, cre]
Maintainer: Alex Yahiaoui Martinez <yahiaoui-martinez.alex@outlook.com>
Repository: CRAN
Date/Publication: 2025-09-30 07:20:18 UTC

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Package pdSpecEst updated to version 1.2.6 with previous version 1.2.4 dated 2020-01-08

Title: An Analysis Toolbox for Hermitian Positive Definite Matrices
Description: An implementation of data analysis tools for samples of symmetric or Hermitian positive definite matrices, such as collections of covariance matrices or spectral density matrices. The tools in this package can be used to perform: (i) intrinsic wavelet transforms for curves (1D) or surfaces (2D) of Hermitian positive definite matrices with applications to dimension reduction, denoising and clustering in the space of Hermitian positive definite matrices; and (ii) exploratory data analysis and inference for samples of positive definite matrices by means of intrinsic data depth functions and rank-based hypothesis tests in the space of Hermitian positive definite matrices.
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau@openanalytics.eu>

Diff between pdSpecEst versions 1.2.4 dated 2020-01-08 and 1.2.6 dated 2025-09-30

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 35 files changed, 1395 insertions(+), 661 deletions(-)

More information about pdSpecEst at CRAN
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Package spatialEco updated to version 2.0-3 with previous version 2.0-2 dated 2023-11-17

Title: Spatial Analysis and Modelling Utilities
Description: Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.
Author: Jeffrey S. Evans [aut, cre] , Melanie A. Murphy [ctb], Karthik Ram [ctb]
Maintainer: Jeffrey S. Evans <jeffrey_evans@tnc.org>

Diff between spatialEco versions 2.0-2 dated 2023-11-17 and 2.0-3 dated 2025-09-30

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 spatialEco-2.0-3/spatialEco/DESCRIPTION                   |   13 -
 spatialEco-2.0-3/spatialEco/MD5                           |   40 +--
 spatialEco-2.0-3/spatialEco/NAMESPACE                     |    3 
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 spatialEco-2.0-3/spatialEco/R/cgls_urls.R                 |  153 +-----------
 spatialEco-2.0-3/spatialEco/R/crossCorrelation.R          |    2 
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 spatialEco-2.0-3/spatialEco/R/elev-data.R                 |    2 
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 spatialEco-2.0-3/spatialEco/R/raster.gaussian.smooth.R    |   69 +++--
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Package prolsirm updated to version 0.1.1 with previous version 0.1.0 dated 2023-09-20

Title: Procrustes Matching for Latent Space Item Response Model
Description: Procrustes matching of the posterior samples of person and item latent positions from latent space item response models. The methods implemented in this package are based on work by Borg, I., Groenen, P. (1997, ISBN:978-0-387-94845-4), Jeon, M., Jin, I. H., Schweinberger, M., Baugh, S. (2021) <doi:10.1007/s11336-021-09762-5>, and Andrew, D. M., Kevin M. Q., Jong Hee Park. (2011) <doi:10.18637/jss.v042.i09>.
Author: Jinwen Luo [aut, cre] , Minjeong Jeon [aut]
Maintainer: Jinwen Luo <jevanluo@ucla.edu>

Diff between prolsirm versions 0.1.0 dated 2023-09-20 and 0.1.1 dated 2025-09-30

 DESCRIPTION       |   10 +++++-----
 MD5               |    6 +++---
 R/procrustes.R    |    6 ++++--
 man/procrustes.Rd |   13 ++++++++-----
 4 files changed, 20 insertions(+), 15 deletions(-)

More information about prolsirm at CRAN
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