Thu, 11 Dec 2025

Package csmpv updated to version 1.0.5 with previous version 1.0.3 dated 2024-03-01

Title: Biomarker Confirmation, Selection, Modelling, Prediction, and Validation
Description: There are diverse purposes such as biomarker confirmation, novel biomarker discovery, constructing predictive models, model-based prediction, and validation. It handles binary, continuous, and time-to-event outcomes at the sample or patient level. - Biomarker confirmation utilizes established functions like glm() from 'stats', coxph() from 'survival', surv_fit(), and ggsurvplot() from 'survminer'. - Biomarker discovery and variable selection are facilitated by three LASSO-related functions LASSO2(), LASSO_plus(), and LASSO2plus(), leveraging the 'glmnet' R package with additional steps. - Eight versatile modeling functions are offered, each designed for predictive models across various outcomes and data types. 1) LASSO2(), LASSO_plus(), LASSO2plus(), and LASSO2_reg() perform variable selection using LASSO methods and construct predictive models based on selected variables. 2) XGBtraining() employs 'XGBoost' for model building and is the only function not involving variable selection. 3 [...truncated...]
Author: Aixiang Jiang [aut, cre, cph]
Maintainer: Aixiang Jiang <aijiang@bccrc.ca>

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Package xtdml updated to version 0.1.11 with previous version 0.1.10 dated 2025-12-10

Title: Double Machine Learning for Static Panel Models with Fixed Effects
Description: The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) <doi:10.1093/ectj/utaf011>. 'xtdml' is built on the object-oriented package 'DoubleML' (Bach et al., 2024) <doi:10.18637/jss.v108.i03> using the 'mlr3' ecosystem.
Author: Annalivia Polselli [aut, cre]
Maintainer: Annalivia Polselli <apolselli.econ@gmail.com>

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Package tepr updated to version 1.1.13 with previous version 1.1.12 dated 2025-11-04

Title: Transcription Elongation Profiling
Description: The general principle relies on calculating the cumulative signal of nascent RNA sequencing over the gene body of any given gene or transcription unit. 'tepr' can identify transcription attenuation sites by comparing profile to a null model which assumes uniform read density over the entirety of the transcription unit. It can also identify increased or diminished transcription attenuation by comparing two conditions. Besides rigorous statistical testing and high sensitivity, a major feature of 'tepr' is its ability to provide the elongation pattern of each individual gene, including the position of the main attenuation point when such a phenomenon occurs. Using 'tepr', users can visualize and refine genome-wide aggregated analyses of elongation patterns to robustly identify effects specific to subsets of genes. These metrics are suitable for internal comparisons (between genes in each condition) and for studying elongation of the same gene in different conditions or comparing it to a p [...truncated...]
Author: Nicolas Descostes [cre], Victor Billon [aut], Gael Cristofari [aut]
Maintainer: Nicolas Descostes <nicolas.descostes@gmail.com>

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Package geomander readmission to version 2.5.2 with previous version 2.5.0 dated 2025-09-01

Title: Geographic Tools for Studying Gerrymandering
Description: A compilation of tools to complete common tasks for studying gerrymandering. This focuses on the geographic tool side of common problems, such as linking different levels of spatial units or estimating how to break up units. Functions exist for creating redistricting-focused data for the US.
Author: Christopher T. Kenny [aut, cre] , Cory McCartan [ctb]
Maintainer: Christopher T. Kenny <ctkenny@proton.me>

This is a re-admission after prior archival of version 2.5.0 dated 2025-09-01

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Package geeLite updated to version 1.0.6 with previous version 1.0.5 dated 2025-12-09

Title: Building and Managing Local Databases from 'Google Earth Engine'
Description: Simplifies the creation, management, and updating of local databases using data extracted from 'Google Earth Engine' ('GEE'). It integrates with 'GEE' to store, aggregate, and process spatio-temporal data, leveraging 'SQLite' for efficient, serverless storage. The 'geeLite' package provides utilities for data transformation and supports real-time monitoring and analysis of geospatial features, making it suitable for researchers and practitioners in geospatial science. For details, see Kurbucz and Andrée (2025) "Building and Managing Local Databases from Google Earth Engine with the geeLite R Package" <https://hdl.handle.net/10986/43165>.
Author: Marcell T. Kurbucz [aut, cre], Bo Pieter Johannes Andree [aut]
Maintainer: Marcell T. Kurbucz <m.kurbucz@ucl.ac.uk>

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Package ddml updated to version 0.3.1 with previous version 0.3.0 dated 2024-10-02

Title: Double/Debiased Machine Learning
Description: Estimate common causal parameters using double/debiased machine learning as proposed by Chernozhukov et al. (2018) <doi:10.1111/ectj.12097>. 'ddml' simplifies estimation based on (short-)stacking as discussed in Ahrens et al. (2024) <doi:10.1002/jae.3103>, which leverages multiple base learners to increase robustness to the underlying data generating process.
Author: Achim Ahrens [aut], Christian B Hansen [aut], Mark E Schaffer [aut], Thomas Wiemann [aut, cre]
Maintainer: Thomas Wiemann <thomas.wiemann@chicagobooth.edu>

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Package baker readmission to version 1.0.4 with previous version 1.0.3 dated 2024-01-30

Title: "Nested Partially Latent Class Models"
Description: Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.
Author: Zhenke Wu [cre, aut, cph] , Scott Zeger [aut] , John Muschelli [ctb] , Irena Chen [ctb]
Maintainer: Zhenke Wu <zhenkewu@gmail.com>

This is a re-admission after prior archival of version 1.0.3 dated 2024-01-30

Diff between baker versions 1.0.3 dated 2024-01-30 and 1.0.4 dated 2025-12-11

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Package serocalculator updated to version 1.4.0 with previous version 1.3.0 dated 2025-01-25

Title: Estimating Infection Rates from Serological Data
Description: Translates antibody levels measured in cross-sectional population samples into estimates of the frequency with which seroconversions (infections) occur in the sampled populations. Replaces the previous `seroincidence` package.
Author: Kristina Lai [aut, cre], Chris Orwa [aut], Kwan Ho Lee [ctb], Peter Teunis [aut, cph] , Kristen Aiemjoy [aut], Douglas Ezra Morrison [aut]
Maintainer: Kristina Lai <kwlai@ucdavis.edu>

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More information about serocalculator at CRAN
Permanent link

Package resilience updated to version 2025.1.0 with previous version 2024.1.2 dated 2024-08-22

Title: Predictors of Resilience to a Stressor in a Single-Arm Study
Description: Studies of resilience in older adults employ a single-arm design where everyone experiences the stressor. The simplistic approach of regressing change versus baseline yields biased estimates due to regression-to-the-mean. This package provides a method to correct the bias. It also allows covariates to be included. The method implemented in the package is described in Varadhan, R., Zhu, J., and Bandeen-Roche, K (2024), Biostatistics 25(4): 1094-1111.
Author: Ravi Varadhan [aut, cre], Jiafeng Zhu [ctb]
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

Diff between resilience versions 2024.1.2 dated 2024-08-22 and 2025.1.0 dated 2025-12-11

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More information about resilience at CRAN
Permanent link

Package stochtree updated to version 0.2.1 with previous version 0.2.0 dated 2025-11-22

Title: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference
Description: Flexible stochastic tree ensemble software. Robust implementations of Bayesian Additive Regression Trees (BART) Chipman, George, McCulloch (2010) <doi:10.1214/09-AOAS285> for supervised learning and Bayesian Causal Forests (BCF) Hahn, Murray, Carvalho (2020) <doi:10.1214/19-BA1195> for causal inference. Enables model serialization and parallel sampling and provides a low-level interface for custom stochastic forest samplers.
Author: Drew Herren [aut, cre] , Richard Hahn [aut], Jared Murray [aut], Carlos Carvalho [aut], Jingyu He [aut], Pedro Lima [ctb], stochtree contributors [cph], Eigen contributors [cph] , xgboost contributors [cph] , treelite contributors [cph] , Microsoft C [...truncated...]
Maintainer: Drew Herren <drewherrenopensource@gmail.com>

Diff between stochtree versions 0.2.0 dated 2025-11-22 and 0.2.1 dated 2025-12-11

 DESCRIPTION                            |    6 
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New package varPro with initial version 1.0.0
Package: varPro
Version: 1.0.0
Date: 2025-12-07
Title: Model-Independent Variable Selection via the Rule-Based Variable Priority
Author: Min Lu [aut], Aster K. Shear [aut], Udaya B. Kogalur [aut, cre], Hemant Ishwaran [aut]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>
BugReports: https://github.com/kogalur/varPro/issues/
Depends: R (>= 4.3.0),
Imports: randomForestSRC (>= 3.4.5), glmnet, parallel, foreach, gbm, BART, umap, survival
Suggests: mlbench, doMC, caret, MASS, igraph
SystemRequirements: OpenMP
Description: A new framework of variable selection, which instead of generating artificial covariates such as permutation importance and knockoffs, creates release rules to examine the affect on the response for each covariate where the conditional distribution of the response variable can be arbitrary and unknown.
License: GPL (>= 3)
URL: https://www.varprotools.org/ https://www.luminwin.net/ https://ishwaran.org/
NeedsCompilation: yes
Packaged: 2025-12-07 19:10:31 UTC; kogalur
Repository: CRAN
Date/Publication: 2025-12-11 19:20:02 UTC

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Package tgml updated to version 0.3.0 with previous version 0.2.0 dated 2025-09-24

Title: Tree Guided Machine Learning for Personalized Predictions and Precision Diagnostics
Description: Generalization of the classification and regression tree (CART) model that partitions subjects into terminal nodes and tailors machine learning model to each terminal node.
Author: Yunro Chung [aut, cre]
Maintainer: Yunro Chung <yunro.chung@asu.edu>

Diff between tgml versions 0.2.0 dated 2025-09-24 and 0.3.0 dated 2025-12-11

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New package jollofR with initial version 0.6.4
Package: jollofR
Title: Small Area Population Estimation by Demographics
Version: 0.6.4
Description: Automatic disaggregation of small1area population estimates by demographic groups (e.g., age, sex, race, marital status, educational level, etc) along with the estimates of uncertainty, using advanced Bayesian statistical modelling approaches based on integrated nested Laplace approximation (INLA) Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> and stochastic partial differential equation (SPDE) methods Lindgren et al. (2011) <doi:10.1111/j.1467-9868.2011.00777.x>. The package implements hierarchical Bayesian modeling frameworks for small area estimation as described in Leasure et al. (2020) <doi:10.1073/pnas.1913050117> and Nnanatu et al. (2025) <doi:10.1038/s41467-025-59862-4>.
License: MIT + file LICENSE
URL: https://github.com/wpgp/jollofR/, https://wpgp.github.io/jollofR/
BugReports: https://github.com/wpgp/jollofR/issues
Depends: R (>= 4.1.0)
Additional_repositories: https://inla.r-inla-download.org/R/stable/
Imports: terra, raster, ggplot2, dplyr, tidyr, sf, ggpubr, reshape2, utils
Suggests: INLA, withr, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2025-12-07 19:21:35 UTC; mohamedyusuf
Author: Chibuzor Christopher Nnanatu [aut, cre] , Mohamed A. Yusuf [aut] , Somnath Chaudhuri [aut] , Ortis Yankey [aut] , Attila N Lazar [aut] , Andrew J Tatem [aut]
Maintainer: Chibuzor Christopher Nnanatu <cc.nnanatu@soton.ac.uk>
Repository: CRAN
Date/Publication: 2025-12-11 19:20:07 UTC

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New package joinless with initial version 0.0.1
Package: joinless
Title: Exploratory Analysis of Relationships Between Variables
Version: 0.0.1
Maintainer: Braylin Alexander Jimenez Reynoso <braylinjr1511@gmail.com>
Description: Provides tools to explore and summarize relationship patterns between variables across one or multiple datasets. The package relies on efficient sampling strategies to estimate pairwise associations and supports quick exploratory data analysis for large or heterogeneous data sources.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), tibble
NeedsCompilation: no
Packaged: 2025-12-07 22:37:54 UTC; Braylin Jimenez
Author: Braylin Alexander Jimenez Reynoso [aut, cre]
Repository: CRAN
Date/Publication: 2025-12-11 19:30:02 UTC

More information about joinless at CRAN
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Package GMAC updated to version 3.2 with previous version 3.1 dated 2022-03-17

Title: Genomic Mediation Analysis with Adaptive Confounding Adjustment
Description: Performs genomic mediation analysis with adaptive confounding adjustment (GMAC) proposed by Yang et al. (2017) <doi:10.1101/gr.216754.116>. It implements large scale mediation analysis and adaptively selects potential confounding variables to adjust for each mediation test from a pool of candidate confounders. The package is tailored for but not limited to genomic mediation analysis (e.g., cis-gene mediating trans-gene regulation pattern where an eQTL, its cis-linking gene transcript, and its trans-gene transcript play the roles as treatment, mediator and the outcome, respectively), restricting to scenarios with the presence of cis-association (i.e., treatment-mediator association) and random eQTL (i.e., treatment).
Author: Fan Yang [aut], Jiebiao Wang [aut, cre], Lin Chen [aut]
Maintainer: Jiebiao Wang <randel.wang@gmail.com>

Diff between GMAC versions 3.1 dated 2022-03-17 and 3.2 dated 2025-12-11

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Package geoprofiler updated to version 0.0.3 with previous version 0.0.2 dated 2025-04-10

Title: Perpendicular Line Transects for Geosciences
Description: Toolset to create perpendicular profile graphs and swath profiles. Method are based on coordinate rotation algorithm by Schaeben et al. (2024) <doi:10.1002/mma.9823>.
Author: Tobias Stephan [aut, cre]
Maintainer: Tobias Stephan <tobias.stephan1@yahoo.com>

Diff between geoprofiler versions 0.0.2 dated 2025-04-10 and 0.0.3 dated 2025-12-11

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New package GACE with initial version 1.0.0
Package: GACE
Title: Generalized Adaptive Capped Estimator for Time Series Forecasting
Version: 1.0.0
Maintainer: Vinodhkumar Gunasekaran <vinoalles@gmail.com>
Description: Provides deterministic forecasting for weekly, monthly, quarterly, and yearly time series using the Generalized Adaptive Capped Estimator. The method includes preprocessing for missing and extreme values, extraction of multiple growth components (including long-term, short-term, rolling, and drift-based signals), volatility-aware asymmetric capping, optional seasonal adjustment via damped and normalized seasonal factors, and a recursive forecast formulation with moderated growth. The package includes a user-facing forecasting interface and a plotting helper for visualization. Related forecasting background is discussed in Hyndman and Athanasopoulos (2021) <https://otexts.com/fpp3/> and Hyndman and Khandakar (2008) <doi:10.18637/jss.v027.i03>. The method extends classical extrapolative forecasting approaches and is suited for operational and business planning contexts where stability and interpretability are important.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, stats, utils
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr, forecast
VignetteBuilder: knitr
URL: https://github.com/vinoalles/GACE
BugReports: https://github.com/vinoalles/GACE/issues
NeedsCompilation: no
Packaged: 2025-12-07 20:32:14 UTC; vinodhkumargunasekaran
Author: Vinodhkumar Gunasekaran [aut, cre]
Repository: CRAN
Date/Publication: 2025-12-11 19:20:18 UTC

More information about GACE at CRAN
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Package bWGR updated to version 2.2.17 with previous version 2.2.15 dated 2025-11-05

Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, single step (<doi:10.1534/g3.119.400728>), univariate and multivariate (<doi:10.1186/s12711-022-00730-w>, <doi:10.1093/genetics/iyae179>), with optional kernel term and sampling techniques (<doi:10.1186/s12859-017-1582-3>).
Author: Alencar Xavier [aut, cre] , William Muir [aut], David Habier [aut], Kyle Kocak [aut], Shizhong Xu [aut], Katy Rainey [aut]
Maintainer: Alencar Xavier <alenxav@gmail.com>

Diff between bWGR versions 2.2.15 dated 2025-11-05 and 2.2.17 dated 2025-12-11

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Package WARDEN updated to version 2.0.1 with previous version 2.0.0 dated 2025-10-13

Title: Workflows for Health Technology Assessments in R using Discrete EveNts
Description: Toolkit to support and perform discrete event simulations with and without resource constraints in the context of health technology assessments (HTA). The package focuses on cost-effectiveness modelling and aims to be submission-ready to relevant HTA bodies in alignment with 'NICE TSD 15' <https://sheffield.ac.uk/nice-dsu/tsds/patient-level-simulation>. More details an examples can be found in the package website <https://jsanchezalv.github.io/WARDEN/>.
Author: Javier Sanchez Alvarez [aut, cre], Gabriel Lemyre [ctb], Valerie Aponte Ribero [ctb]
Maintainer: Javier Sanchez Alvarez <javiersanchezeco@gmail.com>

Diff between WARDEN versions 2.0.0 dated 2025-10-13 and 2.0.1 dated 2025-12-11

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Package SEMdeep updated to version 1.1.1 with previous version 1.1.0 dated 2025-11-10

Title: Structural Equation Modeling with Deep Neural Network and Machine Learning Algorithms
Description: Training and validation of a custom (or data-driven) Structural Equation Models using Deep Neural Networks or Machine Learning algorithms, which extend the fitting procedures of the 'SEMgraph' R package <doi:10.32614/CRAN.package.SEMgraph>.
Author: Mario Grassi [aut], Barbara Tarantino [cre]
Maintainer: Barbara Tarantino <barbara.tarantino01@universitadipavia.it>

Diff between SEMdeep versions 1.1.0 dated 2025-11-10 and 1.1.1 dated 2025-12-11

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Package cellGeometry updated to version 0.5.7 with previous version 0.5.4 dated 2025-09-15

Title: Geometric Single Cell Deconvolution
Description: Deconvolution of bulk RNA-Sequencing data into proportions of cells based on a reference single-cell RNA-Sequencing dataset using high-dimensional geometric methodology.
Author: Myles Lewis [aut, cre] , Rachel Lau [ctb]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

Diff between cellGeometry versions 0.5.4 dated 2025-09-15 and 0.5.7 dated 2025-12-11

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Package GaussSuppression updated to version 1.2.3 with previous version 1.2.0 dated 2025-09-25

Title: Tabular Data Suppression using Gaussian Elimination
Description: A statistical disclosure control tool to protect tables by suppression using the Gaussian elimination secondary suppression algorithm (Langsrud, 2024) <doi:10.1007/978-3-031-69651-0_6>. A suggestion is to start by working with functions SuppressSmallCounts() and SuppressDominantCells(). These functions use primary suppression functions for the minimum frequency rule and the dominance rule, respectively. Novel functionality for suppression of disclosive cells is also included. General primary suppression functions can be supplied as input to the general working horse function, GaussSuppressionFromData(). Suppressed frequencies can be replaced by synthetic decimal numbers as described in Langsrud (2019) <doi:10.1007/s11222-018-9848-9>.
Author: Oeyvind Langsrud [aut, cre] , Daniel Lupp [aut] , Hege Boevelstad [ctb] , Vidar Norstein Klungre [rev] , Jonas Lindblad [ctb], Statistics Norway [cph]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

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Package feltr updated to version 0.1.0 with previous version 0.0.4 dated 2023-11-05

Title: Access the Felt API
Description: Upload, download, and edit internet maps with the Felt API (<https://developers.felt.com/rest-api/getting-started>). Allows users to create new maps, edit existing maps, and extract data. Provides tools for working with layers, which represent geographic data, and elements, which are interactive annotations. Spatial data accessed from the API is transformed to work with 'sf'.
Author: Christopher T. Kenny [aut, cre]
Maintainer: Christopher T. Kenny <ctkenny@proton.me>

Diff between feltr versions 0.0.4 dated 2023-11-05 and 0.1.0 dated 2025-12-11

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Package ergm.sign updated to version 0.1.1 with previous version 0.1.0 dated 2025-11-21

Title: Exponential-Family Models for Signed Networks
Description: Extends the 'ergm.multi' packages from the Statnet suite to fit (temporal) exponential-family random graph models for signed networks. The framework models positive and negative ties as interdependent, which allows estimation and testing of structural balance theory. The package also includes options for descriptive summaries, visualization, and simulation of signed networks. See Krivitsky, Koehly, and Marcum (2020) <doi:10.1007/s11336-020-09720-7> and Fritz, C., Mehrl, M., Thurner, P. W., & Kauermann, G. (2025) <doi:10.1017/pan.2024.21>.
Author: Marc Schalberger [cre], Cornelius Fritz [aut], Pavel Krivitsky [ctb]
Maintainer: Marc Schalberger <m.schalberger@fu-berlin.de>

Diff between ergm.sign versions 0.1.0 dated 2025-11-21 and 0.1.1 dated 2025-12-11

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Package diemr updated to version 1.5.2 with previous version 1.5.1 dated 2025-10-09

Title: Genome Polarization via Diagnostic Index Expectation Maximization
Description: Implements a likelihood-based method for genome polarization, identifying which alleles of SNV markers belong to either side of a barrier to gene flow. The approach co-estimates individual assignment, barrier strength, and divergence between sides, with direct application to studies of hybridization. Includes VCF-to-diem conversion and input checks, support for mixed ploidy and parallelization, and tools for visualization and diagnostic outputs. Based on diagnostic index expectation maximization as described in Baird et al. (2023) <doi:10.1111/2041-210X.14010>.
Author: Natalia Martinkova [aut, cre] , Stuart Baird [aut]
Maintainer: Natalia Martinkova <martinkova@ivb.cz>

Diff between diemr versions 1.5.1 dated 2025-10-09 and 1.5.2 dated 2025-12-11

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Package codalm updated to version 0.1.3 with previous version 0.1.2 dated 2021-07-26

Title: Transformation-Free Linear Regression for Compositional Outcomes and Predictors
Description: Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2022) <doi:10.1111/biom.13465> for transformation-free linear regression for compositional outcomes and predictors.
Author: Jacob Fiksel [aut] , Abhirup Datta [ctb], Sandipan Pramanik [cre, ctb]
Maintainer: Sandipan Pramanik <sandy.pramanik@gmail.com>

Diff between codalm versions 0.1.2 dated 2021-07-26 and 0.1.3 dated 2025-12-11

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Package bibliometrix updated to version 5.2.1 with previous version 5.2.0 dated 2025-11-08

Title: Comprehensive Science Mapping Analysis
Description: Tool for quantitative research in scientometrics and bibliometrics. It implements the comprehensive workflow for science mapping analysis proposed in Aria M. and Cuccurullo C. (2017) <doi:10.1016/j.joi.2017.08.007>. 'bibliometrix' provides various routines for importing bibliographic data from 'SCOPUS', 'Clarivate Analytics Web of Science' (<https://www.webofknowledge.com/>), 'Digital Science Dimensions' (<https://www.dimensions.ai/>), 'OpenAlex' (<https://openalex.org/>), 'Cochrane Library' (<https://www.cochranelibrary.com/>), 'Lens' (<https://lens.org>), and 'PubMed' (<https://pubmed.ncbi.nlm.nih.gov/>) databases, performing bibliometric analysis and building networks for co-citation, coupling, scientific collaboration and co-word analysis.
Author: Massimo Aria [cre, aut, cph] , Corrado Cuccurullo [aut]
Maintainer: Massimo Aria <aria@unina.it>

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Package BayesNSGP updated to version 0.2.0 with previous version 0.1.2 dated 2022-01-08

Title: Bayesian Analysis of Non-Stationary Gaussian Process Models
Description: Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes can be specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary Gaussian processes are a special case of our methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial data sets (Finley, et al (2017) <doi:10.48550/arXiv.1702.00434>). Bayesian inference is carried out using Markov chain Monte Carlo methods via the "nimble" package, and posterior prediction for the Gaussian process at unobserved locations is provided as a post-processing step.
Author: Daniel Turek [aut, cre], Mark Risser [aut]
Maintainer: Daniel Turek <danielturek@gmail.com>

Diff between BayesNSGP versions 0.1.2 dated 2022-01-08 and 0.2.0 dated 2025-12-11

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Package bartCause updated to version 1.0-10 with previous version 1.0-9 dated 2024-09-16

Title: Causal Inference using Bayesian Additive Regression Trees
Description: Contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) <doi:10.1198/jcgs.2010.08162>).
Author: Vincent Dorie [aut, cre] , Jennifer Hill [aut]
Maintainer: Vincent Dorie <vdorie@gmail.com>

Diff between bartCause versions 1.0-9 dated 2024-09-16 and 1.0-10 dated 2025-12-11

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New package yaml12 with initial version 0.1.0
Package: yaml12
Title: Fast 'YAML' 1.2 Parser and Formatter
Version: 0.1.0
Description: A fast, correct, safe, and ergonomic 'YAML' 1.2 parser and generator written in 'Rust'. Convert between 'YAML' and simple 'R' objects with full support for multi-document streams, tags, anchors, and aliases. Offers opt-in handlers for custom tag behavior and round-trips common 'R' data structures. Implements the 'YAML' 1.2.2 specification from the 'YAML' Language Development Team (2021) <https://yaml.org/spec/1.2.2/>. Proudly supported by Posit.
License: MIT + file LICENSE
URL: https://posit-dev.github.io/r-yaml12/, https://github.com/posit-dev/r-yaml12
BugReports: https://github.com/posit-dev/r-yaml12/issues
Depends: R (>= 4.2)
Suggests: jsonlite, knitr, rmarkdown, testthat (>= 3.0.0), waldo, withr
VignetteBuilder: knitr
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.70.0, xz
NeedsCompilation: yes
Packaged: 2025-12-03 19:56:58 UTC; tomasz
Author: Tomasz Kalinowski [aut, cre], Posit Software, PBC [cph, fnd] , Authors of the dependency Rust crates [cph]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>
Repository: CRAN
Date/Publication: 2025-12-11 15:50:02 UTC

More information about yaml12 at CRAN
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Package proxy updated to version 0.4-28 with previous version 0.4-27 dated 2022-06-09

Title: Distance and Similarity Measures
Description: Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones.
Author: David Meyer [aut, cre] , Christian Buchta [aut]
Maintainer: David Meyer <David.Meyer@R-project.org>

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Package lime updated to version 0.5.4 with previous version 0.5.3 dated 2022-08-19

Title: Local Interpretable Model-Agnostic Explanations
Description: When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <doi:10.48550/arXiv.1602.04938>.
Author: Emil Hvitfeldt [aut, cre] , Thomas Lin Pedersen [aut] , Michael Benesty [aut]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

Diff between lime versions 0.5.3 dated 2022-08-19 and 0.5.4 dated 2025-12-11

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Package lessR updated to version 4.5 with previous version 4.4.5 dated 2025-08-22

Title: Less Code with More Comprehensive Results
Description: Each function replaces multiple standard R functions. For example, two function calls, Read() and CountAll(), generate summary statistics for all variables in the data frame, plus histograms and bar charts. Other functions provide data aggregation via pivot tables; comprehensive regression, ANOVA, and t-test; visualizations including integrated Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve; reading multiple data formats with the same call; variable labels; time series with aggregation and forecasting; color themes; and Trellis (facet) graphics. Also includes a confirmatory factor analysis of multiple-indicator measurement models, pedagogical routines for data simulation (e.g., Central Limit Theorem), generation and rendering of regression instructions for interpretative output, and both interactive construction of visualizations and interactive visualizations with plotly.
Author: David W. Gerbing [aut, cre]
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package aorsf updated to version 0.1.6 with previous version 0.1.5 dated 2024-05-29

Title: Accelerated Oblique Random Forests
Description: Fit, interpret, and compute predictions with oblique random forests. Includes support for partial dependence, variable importance, passing customized functions for variable importance and identification of linear combinations of features. Methods for the oblique random survival forest are described in Jaeger et al., (2023) <DOI:10.1080/10618600.2023.2231048>.
Author: Byron Jaeger [aut, cre] , Nicholas Pajewski [ctb], Sawyer Welden [ctb], Christopher Jackson [rev], Marvin Wright [rev], Lukas Burk [rev]
Maintainer: Byron Jaeger <byron.jaeger@gmail.com>

Diff between aorsf versions 0.1.5 dated 2024-05-29 and 0.1.6 dated 2025-12-11

 DESCRIPTION                             |   15 
 LICENSE                                 |    4 
 MD5                                     |  124 +--
 NEWS.md                                 |  274 ++++---
 R/bibentries.R                          |  252 +++----
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 R/coerce_nans.R                         |    4 
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 R/data-pbc_orsf.R                       |   86 +-
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 R/orsf_data_prep.R                      |  111 +--
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 63 files changed, 5583 insertions(+), 5320 deletions(-)

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New package FRCI with initial version 0.1.0
Package: FRCI
Title: Fuzzy & Randomized Confidence Intervals
Version: 0.1.0
Description: Contains the methods proposed by Geyer and Meeden (2005)<doi:10.1214/088342305000000340> and Trigo et al. (2025) <doi:10.47749/T/UNICAMP.2025.1500297> to construct fuzzy confidence intervals. Compute and plot the fuzzy membership functions of the methods, and the expected length compared with the infimum.
License: GPL-3
Imports: DescTools, calculus, ump, zipfR, graphics, stats
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-12-07 01:45:50 UTC; caetn
Author: Carlos Henrique Trigo Nasser Felix [aut, cre], Nancy Garcia [aut], Alex Sousa [aut]
Maintainer: Carlos Henrique Trigo Nasser Felix <c214344@dac.unicamp.br>
Repository: CRAN
Date/Publication: 2025-12-11 14:10:02 UTC

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New package wsMed with initial version 1.0.2
Package: wsMed
Title: Within-Subject Mediation Analysis Using Structural Equation Modeling
Version: 1.0.2
Description: Within-subject mediation analysis using structural equation modeling. Examine how changes in an outcome variable between two conditions are mediated through one or more variables. Supports within-subject mediation analysis using the 'lavaan' package by Rosseel (2012) <doi:10.18637/jss.v048.i02>, and extends Monte Carlo confidence interval estimation to missing data scenarios using the 'semmcci' package by Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Encoding: UTF-8
Suggests: rmarkdown, devtools, testthat
Imports: knitr, lavaan, semmcci, mice, semboottools, MASS, rlang, dplyr, ggplot2, methods, stats
VignetteBuilder: knitr
LazyData: true
URL: https://yangzhen1999.github.io/wsMed/
BugReports: https://github.com/Yangzhen1999/wsMed/issues
NeedsCompilation: no
Packaged: 2025-12-06 12:34:07 UTC; Administrator
Author: Wendie Yang [aut, cre] , Shu Fai Cheung [aut]
Maintainer: Wendie Yang <1581075494q@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-11 13:30:02 UTC

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New package svgedit with initial version 1.0.0
Package: svgedit
Title: Insert Graphs, Images and Text in SVG Files
Version: 1.0.0
Description: Edit SVG files created in 'Inkscape' by replacing placeholders (e.g. a rectangle element or {} in a text box) by 'ggplot2' objects, images or text. This helps automate the creation of figures with complex layouts.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, rlang, xml2, ggplot2, base64enc
Suggests: palmerpenguins, testthat (>= 3.0.0), svglite, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/DanielThedie/svgedit
BugReports: https://github.com/DanielThedie/svgedit/issues
NeedsCompilation: no
Packaged: 2025-12-06 17:09:41 UTC; daniel
Author: Daniel Thedie [aut, cre, cph]
Maintainer: Daniel Thedie <daniel.thedie@ed.ac.uk>
Repository: CRAN
Date/Publication: 2025-12-11 13:50:02 UTC

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New package survlab with initial version 0.1.0
Package: survlab
Title: Survival Model-Based Imputation for Laboratory Non-Detect Data
Version: 0.1.0
Description: Implements survival-model-based imputation for censored laboratory measurements, including Tobit-type models with several distribution options. Suitable for data with values below detection or quantification limits, the package identifies the best-fitting distribution and produces realistic imputations that respect the censoring thresholds.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: data.table (>= 1.17.0), stats, survival (>= 3.0.0), truncnorm (>= 1.0.0)
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
URL: https://lpereira-ue.github.io/survlab/, https://github.com/lpereira-ue/survlab
NeedsCompilation: no
Packaged: 2025-12-06 16:28:23 UTC; lpereira
Author: Luis Pereira [aut, cre] , Paulo Infante [aut] , Teresa Ferreira [ths] , Paulo Quaresma [ths]
Maintainer: Luis Pereira <d57177@alunos.uevora.pt>
Repository: CRAN
Date/Publication: 2025-12-11 13:40:02 UTC

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New package Ruido with initial version 1.0.0
Package: Ruido
Title: Soundscape Background Noise, Power, and Saturation
Version: 1.0.0
Description: Accessible and flexible implementation of three ecoacoustic indices that are less commonly available in existing R frameworks: Background Noise, Soundscape Power and Soundscape Saturation. The functions were design to accommodate a variety of sampling designs. Users can tailor calculations by specifying spectrogram time bin size, amplitude thresholds and normality tests. By simplifying computation and standardizing reproducible methods, the package aims to support ecoacoustics studies. For more details about the indices read Towsey (2014) <doi:10.1016/j.procs.2014.05.063> and Burivalova (2017) <doi:10.1111/cobi.12968>.
Depends: R(>= 4.3.0)
Imports: methods, tuneR, signal, nortest
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: ggplot2, spelling
Maintainer: Arthur Igor da Fonseca-Freire <arthur.igorr@gmail.com>
BugReports: https://github.com/Arthurigorr/Ruido/issues
URL: https://github.com/Arthurigorr/Ruido
Language: en-US
NeedsCompilation: no
Packaged: 2025-12-05 19:32:59 UTC; arthurigorr
Author: Arthur Igor da Fonseca-Freire [aut, cre, cph], Weslley Geremias dos Santos [ctb], Lucas Rodriguez Forti [ctb]
Repository: CRAN
Date/Publication: 2025-12-11 13:30:19 UTC

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New package nadaverse with initial version 0.1.0
Package: nadaverse
Title: Browse Microdata Catalogs Using 'NADA' REST API
Version: 0.1.0
Date: 2025-11-18
Description: Provides a unified, programmatic interface for searching, browsing, and retrieving metadata from various international organization data repositories that use the National Data Archive ('NADA') software, such as the World Bank, 'FAO', and the International Household Survey Network ('IHSN'). Functions allow users to discover available data collections, country codes, and access types, perform complex searches using keyword and spatial/temporal filters, and retrieve detailed study information, including file lists and variable-level data dictionaries. It simplifies access to microdata for researchers and policy analysts globally.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, httr2
URL: https://github.com/guturago/nadaverse
BugReports: https://github.com/guturago/nadaverse/issues
Suggests: httptest2, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-12-06 19:11:17 UTC; Gute
Author: Gutama Girja Urago [aut, cre, cph]
Maintainer: Gutama Girja Urago <girjagutama@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-11 13:50:07 UTC

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New package modernBoot with initial version 0.1.1
Package: modernBoot
Title: Modern Resampling Methods: Bootstraps, Wild, Block, Permutation, and Selection Guidance
Version: 0.1.1
Description: Implements modern resampling and permutation methods for robust statistical inference without restrictive parametric assumptions. Provides bias-corrected and accelerated (BCa) bootstrap (Efron and Tibshirani (1993) <doi:10.1201/9780429246593>), wild bootstrap for heteroscedastic regression (Liu (1988) <doi:10.1214/aos/1176351062>, Davidson and Flachaire (2008) <doi:10.1016/j.jeconom.2008.08.003>), block bootstrap for time series (Politis and Romano (1994) <doi:10.1080/01621459.1994.10476870>), and permutation-based multiple testing correction (Westfall and Young (1993) <ISBN:0-471-55761-7>). Methods handle non-normal data, heteroscedasticity, time series correlation, and multiple comparisons.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: stats, boot, future, future.apply
Suggests: testthat (>= 3.0.0), covr, pkgdown, rhub
URL: https://github.com/ikrakib/modernBoot
BugReports: https://github.com/ikrakib/modernBoot/issues
NeedsCompilation: no
Packaged: 2025-12-06 18:34:53 UTC; hello
Author: Ibrahim Kholil Rakib [aut, cre]
Maintainer: Ibrahim Kholil Rakib <ikrakib1010@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-11 13:50:13 UTC

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New package irls with initial version 1.0
Package: irls
Title: Generalised Linear Models via Iteratively Reweighted Least Squares
Version: 1.0
Author: Michail Tsagris [aut, cre], Nikolaos Kontemeniotis [aut], Christos Adam [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Description: Generalised linear models via the iteratively reweighted least squares algorithm. The functions perform logistic, Poisson and Gamma regression (ISBN:9780412317606), either for a single model or many regression models in a column-wise fashion.
License: GPL (>= 2)
Depends: R (>= 4.2)
Imports: Rcpp (>= 1.0.13)
LinkingTo: Rcpp (>= 1.0.13), RcppEigen
Suggests: Rfast, Rfast2
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-12-06 13:43:54 UTC; Administrator
Repository: CRAN
Date/Publication: 2025-12-11 13:40:07 UTC

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New package impermanentlosscalc with initial version 0.1.0
Package: impermanentlosscalc
Title: Calculate Impermanent Loss in Automated Market Maker (AMM) Liquidity Pools
Version: 0.1.0
Description: Computes the key metrics for assessing the performance of a liquidity provider (LP) position in a weighted multi-asset Automated Market Maker (AMM) pool. Calculates the nominal and percentage impermanent loss (IL) by comparing the portfolio value inside the pool (based on the weighted geometric mean of price ratios) against the value of simply holding the assets outside the pool (based on the weighted arithmetic mean). The primary function, `impermanent_loss()`, incorporates the effect of earned trading fees to provide the LP's net profit and loss relative to a holding strategy, using a methodology derived from Tiruviluamala, N., Port, A., and Lewis, E. (2022) <doi:10.48550/arXiv.2203.11352>.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-06 16:06:01 UTC; amber
Author: Amber Krause [aut, cre]
Maintainer: Amber Krause <amber32k@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-11 13:40:11 UTC

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New package hypothesize with initial version 0.10.0
Package: hypothesize
Title: A Consistent API for Hypothesis Testing
Version: 0.10.0
Description: Provides a consistent API for hypothesis testing built on principles from 'Structure and Interpretation of Computer Programs': data abstraction, closure (combining tests yields tests), and higher-order functions (transforming tests). Implements z-tests, Wald tests, likelihood ratio tests, Fisher's method for combining p-values, and multiple testing corrections. Designed for use by other packages that want to wrap their hypothesis tests in a consistent interface.
Encoding: UTF-8
Maintainer: Alexander Towell <lex@metafunctor.com>
License: MIT + file LICENSE
ByteCompile: true
Imports: stats
URL: https://github.com/queelius/hypothesize, https://queelius.github.io/hypothesize/
BugReports: https://github.com/queelius/hypothesize/issues
Suggests: testthat (>= 3.0.0), rmarkdown, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-05 18:08:28 UTC; spinoza
Author: Alexander Towell [aut, cre]
Repository: CRAN
Date/Publication: 2025-12-11 13:20:02 UTC

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New package fjoin with initial version 0.1.0
Package: fjoin
Title: Data Frame Joins Leveraging 'data.table'
Version: 0.1.0
Description: Extends 'data.table' join functionality, lets it work with any data frame class, and provides a familiar 'x'/'y'-style interface, enabling broad use across R. Offers NA-safe matching by default, on-the-fly column selection, multiple match-handling on both sides, 'x' or 'y' row order, and a row origin indicator. Performs inner, left, right, full, semi- and anti-joins with equality and inequality conditions, plus cross joins. Specific support for 'data.table', (grouped) tibble, and 'sf'/'sfc' objects and their attributes; returns a plain data frame otherwise. Avoids data-copying of inputs and outputs. Allows displaying the 'data.table' code instead of (or as well as) executing it.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.3.0)
Imports: data.table
Suggests: dplyr (>= 1.1.0), sf, testthat (>= 3.0.0), knitr, rmarkdown, quarto, bench, ggplot2
URL: https://trobx.github.io/fjoin/
BugReports: https://github.com/trobx/fjoin/issues
VignetteBuilder: knitr, quarto
NeedsCompilation: no
Packaged: 2025-12-05 22:00:23 UTC; Toby
Author: Toby Robertson [aut, cre]
Maintainer: Toby Robertson <trobx@proton.me>
Repository: CRAN
Date/Publication: 2025-12-11 13:30:08 UTC

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Package CoxBoost readmission to version 1.5.1 with previous version 1.4 dated 2013-05-10

Title: Cox Models by Likelihood Based Boosting for a Single Survival Endpoint or Competing Risks
Description: Provides routines for fitting Cox models by likelihood based boosting for single event survival data with right censoring or in the presence of competing risks. The methodology is described in Binder and Schumacher (2008) <doi:10.1186/1471-2105-9-14> and Binder et al. (2009) <doi:10.1093/bioinformatics/btp088>.
Author: John Zobolas [cre, aut] , Harald Binder [aut]
Maintainer: John Zobolas <bblodfon@gmail.com>

This is a re-admission after prior archival of version 1.4 dated 2013-05-10

Diff between CoxBoost versions 1.4 dated 2013-05-10 and 1.5.1 dated 2025-12-11

 CoxBoost-1.4/CoxBoost/R/optimStepSizeFactor.R       |only
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 CoxBoost-1.5.1/CoxBoost/DESCRIPTION                 |   39 
 CoxBoost-1.5.1/CoxBoost/LICENSE                     |only
 CoxBoost-1.5.1/CoxBoost/MD5                         |   50 
 CoxBoost-1.5.1/CoxBoost/NAMESPACE                   |   39 
 CoxBoost-1.5.1/CoxBoost/NEWS.md                     |only
 CoxBoost-1.5.1/CoxBoost/R/CoxBoost.R                | 2144 +++++++++++++++-----
 CoxBoost-1.5.1/CoxBoost/R/estimPVal.R               |  105 
 CoxBoost-1.5.1/CoxBoost/R/iCoxBoost.R               |  379 +++
 CoxBoost-1.5.1/CoxBoost/R/resample.CoxBoost.R       |only
 CoxBoost-1.5.1/CoxBoost/R/zzz.R                     |only
 CoxBoost-1.5.1/CoxBoost/README.md                   |only
 CoxBoost-1.5.1/CoxBoost/build                       |only
 CoxBoost-1.5.1/CoxBoost/inst                        |only
 CoxBoost-1.5.1/CoxBoost/man/CoxBoost-package.Rd     |only
 CoxBoost-1.5.1/CoxBoost/man/CoxBoost.Rd             |  285 ++
 CoxBoost-1.5.1/CoxBoost/man/coef.CoxBoost.Rd        |   26 
 CoxBoost-1.5.1/CoxBoost/man/cv.CoxBoost.Rd          |  150 +
 CoxBoost-1.5.1/CoxBoost/man/cvcb.control.Rd         |   70 
 CoxBoost-1.5.1/CoxBoost/man/estimPVal.Rd            |  101 
 CoxBoost-1.5.1/CoxBoost/man/figures                 |only
 CoxBoost-1.5.1/CoxBoost/man/iCoxBoost.Rd            |  233 +-
 CoxBoost-1.5.1/CoxBoost/man/optimCoxBoostPenalty.Rd |  102 
 CoxBoost-1.5.1/CoxBoost/man/plot.CoxBoost.Rd        |   32 
 CoxBoost-1.5.1/CoxBoost/man/predict.CoxBoost.Rd     |   86 
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 CoxBoost-1.5.1/CoxBoost/src/init.c                  |only
 34 files changed, 3137 insertions(+), 1000 deletions(-)

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New package bpvars with initial version 1.0
Package: bpvars
Title: Forecasting with Bayesian Panel Vector Autoregressions
Description: Provides Bayesian estimation and forecasting of dynamic panel data using Bayesian Panel Vector Autoregressions with hierarchical prior distributions. The models include country-specific VARs that share a global prior distribution that extend the model by Jarociński (2010) <doi:10.1002/jae.1082>. Under this prior expected value, each country's system follows a global VAR with country-invariant parameters. Further flexibility is provided by the hierarchical prior structure that retains the Minnesota prior interpretation for the global VAR and features estimated prior covariance matrices, shrinkage, and persistence levels. Bayesian forecasting is developed for models including exogenous variables, allowing conditional forecasts given the future trajectories of some variables and restricted forecasts assuring that rates are forecasted to stay positive and less than 100. The package implements the model specification, estimation, and forecasting routines, facilitating coherent workflo [...truncated...]
Version: 1.0
Date: 2025-12-02
Maintainer: Tomasz Wozniak <wozniak.tom@pm.me>
License: GPL (>= 3)
Depends: R (>= 4.1.0), bsvars (>= 3.2)
Imports: R6, Rcpp (>= 1.0.12), RcppProgress, RcppTN, tmvtnsim, generics
LinkingTo: bsvars, Rcpp, RcppArmadillo, RcppProgress, RcppTN
Suggests: tinytest
URL: https://bsvars.org/bpvars/
BugReports: https://github.com/bsvars/bpvars/issues
LazyData: true
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-12-03 05:17:02 UTC; twozniak
Author: Tomasz Wozniak [aut, cre] , Miguel Sanchez-Martinez [ctb], International Labour Organization [cph]
Repository: CRAN
Date/Publication: 2025-12-11 14:00:02 UTC

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New package blockr.dock with initial version 0.1.0
Package: blockr.dock
Title: A Docking Layout Manager for 'blockr'
Version: 0.1.0
Description: Building on the docking layout manager provided by 'dockViewR', this provides a flexible front-end to 'blockr.core'. It provides an extension mechanism which allows for providing means to manipulate a board object via panel-based user interface components.
URL: https://bristolmyerssquibb.github.io/blockr.dock/
BugReports: https://github.com/BristolMyersSquibb/blockr.dock/issues
License: GPL (>= 3)
Encoding: UTF-8
Imports: blockr.core (>= 0.1.1), bsicons, shiny, shinyjs, bslib, glue, dockViewR (>= 0.2.1), htmltools, cli, shinyWidgets, jsonlite
Suggests: testthat (>= 3.0.0), DT, colorspace, methods, withr, shinytest2
NeedsCompilation: no
Packaged: 2025-12-06 14:23:01 UTC; nbennett
Author: Nicolas Bennett [aut, cre], David Granjon [aut]
Maintainer: Nicolas Bennett <nicolas@cynkra.com>
Repository: CRAN
Date/Publication: 2025-12-11 13:30:14 UTC

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Package mesonet updated to version 0.0.2 with previous version 0.0.1 dated 2025-07-28

Title: Download and Process Oklahoma Mesonet Data
Description: A collection of functions to download and process weather data from the Oklahoma Mesonet <https://mesonet.org>. Functions are available for downloading station metadata, downloading Mesonet time series (MTS) files, importing MTS files into R, and converting soil temperature change measurements into soil matric potential and volumetric soil moisture.
Author: Phillip D. Alderman [aut, cre]
Maintainer: Phillip D. Alderman <phillip.alderman@okstate.edu>

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Package scCustomize updated to version 3.2.4 with previous version 3.2.3 dated 2025-12-09

Title: Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
Description: Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.
Author: Samuel Marsh [aut, cre] , Ming Tang [ctb], Velina Kozareva [ctb], Lucas Graybuck [ctb], Zoe Clarke [ctb]
Maintainer: Samuel Marsh <sccustomize@gmail.com>

Diff between scCustomize versions 3.2.3 dated 2025-12-09 and 3.2.4 dated 2025-12-11

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Package sars updated to version 2.1.0 with previous version 2.0.0 dated 2025-03-03

Title: Fit and Compare Species-Area Relationship Models Using Multimodel Inference
Description: Implements the basic elements of the multi-model inference paradigm for up to twenty species-area relationship models (SAR), using simple R list-objects and functions, as in Triantis et al. 2012 <DOI:10.1111/j.1365-2699.2011.02652.x>. The package is scalable and users can easily create their own model and data objects. Additional SAR related functions are provided.
Author: Thomas J. Matthews [aut, cre] , Francois Guilhaumon [aut] , Kevin Cazelles [rev]
Maintainer: Thomas J. Matthews <txm676@gmail.com>

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Package plotthis updated to version 0.9.0 with previous version 0.8.2 dated 2025-11-10

Title: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages
Description: Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. It is particularly useful for creating complex plots with multiple layers, facets, and annotations. It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. The API can be found at <https://pwwang.github.io/plotthis/reference/index.html>.
Author: Panwen Wang [aut, cre]
Maintainer: Panwen Wang <pwwang@pwwang.com>

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Package hydroEvents updated to version 0.13.0 with previous version 0.12.0 dated 2025-02-12

Title: Extract Event Statistics in Hydrologic Time Series
Description: Events from individual hydrologic time series are extracted, and events are matched across multiple time series. The package has been applied in studies such as Wasko and Guo (2022) <doi:10.1002/hyp.14563> and Mohammadpour Khoie, Guo and Wasko (2025) <doi:10.1016/j.envsoft.2025.106521>.
Author: Conrad Wasko [aut, cre], Danlu Guo [aut], Mohammad Masoud Mohammadpour Khoie [ctb]
Maintainer: Conrad Wasko <conrad.wasko@gmail.com>

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Package countprop updated to version 1.1.1 with previous version 1.0.1 dated 2023-08-18

Title: Calculate Model-Based Metrics of Proportionality on Count-Based Compositional Data
Description: Calculates metrics of proportionality using the logit-normal multinomial model. It can also provide empirical and plugin estimates of these metrics.
Author: Kevin McGregor [aut, cre, cph], Nneka Okaeme [aut]
Maintainer: Kevin McGregor <kevin.mcgregor@umanitoba.ca>

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Package prettyglm (with last version 1.0.1) was removed from CRAN

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

2023-09-06 1.0.1

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

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

2025-10-27 0.1.1
2024-06-18 0.1.0

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

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Package geomander (with last version 2.5.0) was removed from CRAN

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2025-09-01 2.5.0
2024-02-15 2.3.0
2023-04-16 2.2.1
2022-06-23 2.1.0
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2021-06-16 1.0.8
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Package vip (with last version 0.4.3) was removed from CRAN

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2025-12-10 0.4.3
2025-12-02 0.4.2
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Package radiant (with last version 1.6.6) was removed from CRAN

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2024-05-21 1.6.6
2023-12-17 1.6.1
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Package moreparty (with last version 0.4.2) was removed from CRAN

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2025-09-12 0.4.2
2023-11-22 0.4
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Package flowml (with last version 0.1.3) was removed from CRAN

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2024-02-16 0.1.3
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Package radiant.model (with last version 1.6.8) was removed from CRAN

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2025-10-01 1.6.8
2024-10-11 1.6.7
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Package radiant.multivariate (with last version 1.6.7) was removed from CRAN

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2025-03-10 1.6.7
2024-05-19 1.6.6
2023-09-23 1.6.1
2023-09-11 1.6.0

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Package srppp updated to version 2.0.0 with previous version 1.1.0 dated 2025-07-17

Title: Read the Swiss Register of Plant Protection Products
Description: Generate data objects from XML versions of the Swiss Register of Plant Protection Products. An online version of the register can be accessed at <https://www.psm.admin.ch/de/produkte>. There is no guarantee of correspondence of the data read in using this package with that online version, or with the original registration documents. Also, the Federal Food Safety and Veterinary Office, coordinating the authorisation of plant protection products in Switzerland, does not answer requests regarding this package.
Author: Daniel Baumgartner [ctb] , Marcel Mathis [rev, ctb], Romualdus Kasteel [rev] , Elisabeth Lutz [ctb], Johannes Ranke [aut, cre] , Agroscope [cph]
Maintainer: Johannes Ranke <johannes.ranke@agroscope.admin.ch>

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Package OrgHeatmap updated to version 0.3.2 with previous version 0.3.1 dated 2025-11-26

Title: Visualization Tool for Numerical Data on Human/Mouse Organs and Organelles
Description: A tool for visualizing numerical data (e.g., gene expression, protein abundance) on predefined anatomical maps of human/mouse organs and subcellular organelles. It supports customization of color schemes, filtering by organ systems (for organisms) or organelle types, and generation of optional bar charts for quantitative comparison. The package integrates coordinate data for organs and organelles to plot anatomical/subcellular contours, mapping data values to specific structures for intuitive visualization of biological data distribution.The underlying method was described in the preprint by Zhou et al. (2022) <doi:10.1101/2022.09.07.506938>.
Author: Qirui Shen [aut, cre]
Maintainer: Qirui Shen <shenqr@i.smu.edu.cn>

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Package DIVINE updated to version 0.1.1 with previous version 0.1.0 dated 2025-11-11

Title: Curated Datasets and Tools for Epidemiological Data Analysis
Description: Curated datasets and intuitive data management functions to streamline epidemiological data workflows. It is designed to support researchers in quickly accessing clean, structured data and applying essential cleaning, summarizing, visualization, and export operations with minimal effort. Whether you're preparing a cohort for analysis or creating reports, 'DIVINE' makes the process more efficient, transparent, and reproducible.
Author: Natalia Pallares [aut, cre], Joao Carmezim [aut], Pau Satorra [aut], Lucia Blanc [aut], Cristian Tebe [aut]
Maintainer: Natalia Pallares <npallares@igtp.cat>

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Package vcdExtra updated to version 0.8.7 with previous version 0.8-6 dated 2025-07-24

Title: 'vcd' Extensions and Additions
Description: Provides additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data and the 'gnm' package for Generalized Nonlinear Models. In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and adds a 3D version in 'mosaic3d'. Additionally, methods are provided for comparing and visualizing lists of 'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer.
Author: Michael Friendly [aut, cre] , Heather Turner [ctb], David Meyer [ctb], Achim Zeileis [ctb] , Duncan Murdoch [ctb], David Firth [ctb], Matt Kumar [ctb], Shuguang Sun [ctb], Daniel Sabanes Bove [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package reqres updated to version 1.2.0 with previous version 1.1.0 dated 2025-11-06

Title: Powerful Classes for HTTP Requests and Responses
Description: In order to facilitate parsing of http requests and creating appropriate responses this package provides two classes to handle a lot of the housekeeping involved in working with http exchanges. The infrastructure builds upon the 'rook' specification and is thus well suited to be combined with 'httpuv' based web servers.
Author: Thomas Lin Pedersen [cre, aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between reqres versions 1.1.0 dated 2025-11-06 and 1.2.0 dated 2025-12-11

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Package kendallknight updated to version 1.0.1 with previous version 1.0.0 dated 2025-08-31

Title: Efficient Implementation of Kendall's Correlation Coefficient Computation
Description: The computational complexity of the implemented algorithm for Kendall's correlation is O(n log(n)), which is faster than the base R implementation with a computational complexity of O(n^2). For small vectors (i.e., less than 100 observations), the time difference is negligible. However, for larger vectors, the speed difference can be substantial and the numerical difference is minimal. The references are Knight (1966) <doi:10.2307/2282833>, Abrevaya (1999) <doi:10.1016/S0165-1765(98)00255-9>, Christensen (2005) <doi:10.1007/BF02736122> and Emara (2024) <https://learningcpp.org/>. This implementation is described in Vargas Sepulveda (2025) <doi:10.1371/journal.pone.0326090>.
Author: Mauricio Vargas Sepulveda [aut, cre] , Loader Catherine [ctb] ), Ross Ihaka [ctb] )
Maintainer: Mauricio Vargas Sepulveda <m.vargas.sepulveda@gmail.com>

Diff between kendallknight versions 1.0.0 dated 2025-08-31 and 1.0.1 dated 2025-12-11

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Package firesale updated to version 0.1.1 with previous version 0.1.0 dated 2025-08-27

Title: Datastore for 'fiery' Web Servers
Description: Provides a persistent datastore for 'fiery' apps. The datastore is build on top of the 'storr' package and can thus be based on a variety of backends. The datastore contains both a global and session-scoped section.
Author: Thomas Lin Pedersen [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

Diff between firesale versions 0.1.0 dated 2025-08-27 and 0.1.1 dated 2025-12-11

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Package explore updated to version 1.4.0 with previous version 1.3.6 dated 2025-10-02

Title: Simplifies Exploratory Data Analysis
Description: Interactive data exploration with one line of code, automated reporting or use an easy to remember set of tidy functions for low code exploratory data analysis.
Author: Roland Krasser [aut, cre]
Maintainer: Roland Krasser <roland.krasser@gmail.com>

Diff between explore versions 1.3.6 dated 2025-10-02 and 1.4.0 dated 2025-12-11

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Package cpp11bigwig updated to version 0.1.3 with previous version 0.1.2 dated 2025-08-18

Title: Read bigWig and bigBed Files
Description: Read bigWig and bigBed files using "libBigWig" <https://github.com/dpryan79/libBigWig>. Provides lightweight access to the binary bigWig and bigBed formats developed by the UCSC Genome Browser group.
Author: Jay Hesselberth [aut, cre], RNA Bioscience Initiative [fnd, cph], Devon Ryan [cph]
Maintainer: Jay Hesselberth <jay.hesselberth@gmail.com>

Diff between cpp11bigwig versions 0.1.2 dated 2025-08-18 and 0.1.3 dated 2025-12-11

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Package chillR updated to version 0.77 with previous version 0.76 dated 2024-11-14

Title: Statistical Methods for Phenology Analysis in Temperate Fruit Trees
Description: The phenology of plants (i.e. the timing of their annual life phases) depends on climatic cues. For temperate trees and many other plants, spring phases, such as leaf emergence and flowering, have been found to result from the effects of both cool (chilling) conditions and heat. Fruit tree scientists (pomologists) have developed some metrics to quantify chilling and heat (e.g. see Luedeling (2012) <doi:10.1016/j.scienta.2012.07.011>). 'chillR' contains functions for processing temperature records into chilling (Chilling Hours, Utah Chill Units and Chill Portions) and heat units (Growing Degree Hours). Regarding chilling metrics, Chill Portions are often considered the most promising, but they are difficult to calculate. This package makes it easy. 'chillR' also contains procedures for conducting a PLS analysis relating phenological dates (e.g. bloom dates) to either mean temperatures or mean chill and heat accumulation rates, based on long-term weather and phenology records (Lued [...truncated...]
Author: Eike Luedeling [aut, cre] , Lars Caspersen [aut] , Eduardo Fernandez [aut]
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

Diff between chillR versions 0.76 dated 2024-11-14 and 0.77 dated 2025-12-11

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