Thu, 16 Apr 2026

Package Rmfrac updated to version 1.0.0 with previous version 0.1.1 dated 2025-09-10

Title: Simulation and Statistical Analysis of Multifractional Processes
Description: Simulation of several fractional and multifractional processes. Includes Brownian and fractional Brownian motions, bridges and Gaussian Haar-based multifractional processes (GHBMP). Implements the methods from Ayache, Olenko and Samarakoon (2026) <doi:10.1016/j.matcom.2026.01.033> for simulation of GHBMP. Estimation of Hurst functions and local fractal dimension. Clustering realisations based on the Hurst functions. Several functions to estimate and plot geometric statistics of the processes and time series. Provides a 'shiny' application for interactive use of the functions from the package.
Author: Andriy Olenko [aut] , Nemini Samarakoon [aut, cre]
Maintainer: Nemini Samarakoon <neminisamarakoon95@gmail.com>

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Package quickSentiment updated to version 0.3.4 with previous version 0.3.3 dated 2026-04-01

Title: A Fast and Flexible Pipeline for Text Classification
Description: A high-level pipeline that simplifies text classification into three streamlined steps: preprocessing, model training, and standardized prediction. It unifies the interface for multiple algorithms (including 'glmnet', 'ranger', 'xgboost', and 'naivebayes') and memory-efficient sparse matrix vectorization methods (Bag-of-Words, Term Frequency, TF-IDF, and Binary). Users can go from raw text to a fully evaluated sentiment model, complete with ROC-optimized thresholds, in just a few function calls. The resulting model artifact automatically aligns the vocabulary of new datasets during the prediction phase, safely appending predicted classes and probability matrices directly to the user's original dataframe to preserve metadata.
Author: Alabhya Dahal [aut, cre]
Maintainer: Alabhya Dahal <alabhya.dahal@gmail.com>

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Package bifrost updated to version 0.1.4 with previous version 0.1.3 dated 2026-01-21

Title: Branch-Level Inference Framework for Recognizing Optimal Shifts in Traits
Description: Methods for detecting and visualizing cladogenic shifts in multivariate trait data on phylogenies. Implements penalized-likelihood multivariate generalized least squares models, enabling analyses of high-dimensional trait datasets and large trees via searchOptimalConfiguration(). Includes a greedy step-wise shift-search algorithm following approaches developed in Smith et al. (2023) <doi:10.1111/nph.19099> and Berv et al. (2024) <doi:10.1126/sciadv.adp0114>. Methods build on multivariate GLS approaches described in Clavel et al. (2019) <doi:10.1093/sysbio/syy045> and implemented in the mvgls() function from the 'mvMORPH' package. Documentation and vignettes are available at <https://jakeberv.com/bifrost/>, including worked examples for the jaw-shape dataset.
Author: Jacob S. Berv [aut, cre, cph, fnd] , Nathan Fox [aut] , Matt J. Thorstensen [aut] , Henry Lloyd-Laney [aut] , Emily M. Troyer [aut] , Rafael A. Rivero-Vega [aut] , Stephen A. Smith [aut, fnd] , Matt Friedman [aut, fnd] , David F. Fouhey [aut, fnd] , [...truncated...]
Maintainer: Jacob S. Berv <jacob.berv@gmail.com>

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Package spectrino (with last version 2.0.0) was removed from CRAN

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2019-06-03 2.0.0
2015-07-27 1.6.0
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Package blatr (with last version 1.0.1) was removed from CRAN

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2015-03-11 1.0.1
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Package MDSGUI (with last version 0.1.6) was removed from CRAN

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2014-10-19 0.1.6
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Package MediaNews (with last version 0.2.1) was removed from CRAN

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2020-11-26 0.2.1
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Package BiplotGUI (with last version 0.0-12) was removed from CRAN

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Package taskscheduleR (with last version 1.8) was removed from CRAN

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Package R2PPT (with last version 2.2.0) was removed from CRAN

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Package rFUSION (with last version 0.1) was removed from CRAN

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Package KeyboardSimulator (with last version 2.6.2) was removed from CRAN

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2023-09-13 2.6.2
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2020-03-22 2.1.1
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Package RDesk (with last version 1.0.4) was removed from CRAN

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Package excel.link (with last version 0.9.15) was removed from CRAN

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2018-05-23 0.9.8-1
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2016-09-24 0.9.5
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Package R2wd (with last version 1.5) was removed from CRAN

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Package RWinEdt (with last version 2.0-6) was removed from CRAN

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Package timeperiodsR updated to version 0.7.5 with previous version 0.7.3 dated 2024-01-23

Title: Simple Definition Of Time Intervals
Description: Simple definition of time intervals for the current, previous, and next week, month, quarter and year.
Author: Alexey Seleznev [aut, cre]
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package RALSA updated to version 1.6.6 with previous version 1.6.5 dated 2026-03-17

Title: R Analyzer for Large-Scale Assessments
Description: Download, prepare and analyze data from large-scale assessments and surveys with complex sampling and assessment design (see 'Rutkowski', 2010 <doi:10.3102/0013189X10363170>). Such studies are, for example, international assessments like 'TIMSS', 'PIRLS' and 'PISA'. A graphical interface is available for the non-technical user.The package includes functions to covert the original data from 'SPSS' into 'R' data sets keeping the user-defined missing values, merge data from different respondents and/or countries, generate variable dictionaries, modify data, produce descriptive statistics (percentages, means, percentiles, benchmarks) and multivariate statistics (correlations, linear regression, binary logistic regression). The number of supported studies and analysis types will increase in future. For a general presentation of the package, see 'Mirazchiyski', 2021a (<doi:10.1186/s40536-021-00114-4>). For detailed technical aspects of the package, see 'Mirazchiyski', 2021b (< [...truncated...]
Author: Plamen V. Mirazchiyski [aut, cre]
Maintainer: Plamen V. Mirazchiyski <plamen.mirazchiyski@gmail.com>

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Package multinma updated to version 0.9.1 with previous version 0.9.0 dated 2026-04-13

Title: Bayesian Network Meta-Analysis of Individual and Aggregate Data
Description: Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Author: David M. Phillippo [aut, cre] , Samuel J. Perren [ctb] , Niels Dunnewind [ctb]
Maintainer: David M. Phillippo <david.phillippo@bristol.ac.uk>

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Package RColetum updated to version 1.0.0 with previous version 0.2.2 dated 2022-10-20

Title: Access your Coletum's Data from API
Description: Get your data (forms, structures, answers) from Coletum <https://coletum.com> to handle and analyse.
Author: Andre Smaniotto [aut, cre], Marcelo Magnani [aut], Rodrigo Sant'Ana [aut], GeoSapiens [cph, fnd]
Maintainer: Andre Smaniotto <smaniotto@geosapiens.com.br>

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Package traumar updated to version 1.2.5 with previous version 1.2.4 dated 2026-02-05

Title: Calculate Metrics for Trauma System Performance
Description: Hospitals, hospital systems, and even trauma systems that provide care to injured patients may not be aware of robust metrics that can help gauge the efficacy of their programs in saving the lives of injured patients. 'traumar' provides robust functions driven by the academic literature to automate the calculation of relevant metrics to individuals desiring to measure the performance of their trauma center or even a trauma system. 'traumar' also provides some helper functions for the data analysis journey. Users can refer to the following publications for descriptions of the methods used in 'traumar'. TRISS methodology, including probability of survival, and the W, M, and Z Scores - Flora (1978) <doi:10.1097/00005373-197810000-00003>, Boyd et al. (1987, PMID:3106646), Llullaku et al. (2009) <doi:10.1186/1749-7922-4-2>, Singh et al. (2011) <doi:10.4103/0974-2700.86626>, Baker et al. (1974, PMID:4814394), and Champion et al. (1989) <doi:10.1097/00005373-198905000- [...truncated...]
Author: Nicolas Foss [aut, cre], Iowa Department of Health and Human Services [cph]
Maintainer: Nicolas Foss <nicolas.foss@hhs.iowa.gov>

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Package slideimp updated to version 1.0.0 with previous version 0.5.4 dated 2026-01-07

Title: Numeric Matrices K-NN and PCA Imputation
Description: Fast k-nearest neighbors (K-NN) and principal component analysis (PCA) imputation algorithms for missing values in high-dimensional numeric matrices, i.e., epigenetic data. For extremely high-dimensional data with ordered features, a sliding window approach for K-NN or PCA imputation is provided. Additional features include group-wise imputation (e.g., by chromosome), hyperparameter tuning with repeated cross-validation, multi-core parallelization, and optional subset imputation. The K-NN algorithm is described in: Hastie, T., Tibshirani, R., Sherlock, G., Eisen, M., Brown, P. and Botstein, D. (1999) "Imputing Missing Data for Gene Expression Arrays". The PCA imputation is an optimized version of the imputePCA() function from the 'missMDA' package described in: Josse, J. and Husson, F. (2016) <doi:10.18637/jss.v070.i01> "missMDA: A Package for Handling Missing Values in Multivariate Data Analysis".
Author: Hung Pham [aut, cre, cph]
Maintainer: Hung Pham <amser.hoanghung@gmail.com>

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New package swcEcon with initial version 0.1.0
Package: swcEcon
Title: Economic Analysis of Soil and Water Conservation Measures in Watersheds
Version: 0.1.0
Description: Provides functions and benchmark datasets for the economic appraisal of soil and water conservation (SWC) measures in watershed development projects. Implements benefit-cost ratio (BCR), net present value (NPV), internal rate of return (IRR) via the bisection method of Brent (1973, ISBN:9780130223715), modified BCR, marginal rate of return using the CIMMYT (1988, ISBN:9686127127) method, payback period, soil loss economic valuation via the Universal Soil Loss Equation of Wischmeier and Smith (1978, ISBN:0160016258), groundwater recharge valuation, employment generation ratio, sensitivity analysis, switching value analysis, and Monte Carlo simulation. Six datasets are included: state-wise BCR benchmarks from NABARD (2019) watershed evaluations, USLE erodibility parameters for Indian soil orders from NBSS and LUP, rainfall erosivity for twenty Indian districts from IMD data, SWC unit cost norms from PMKSY-WDC (GoI 2015), and two hypothetical datasets for illustration. Methods follow Gitt [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-13 05:18:42 UTC; acer
Author: Sadikul Islam [aut, cre]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 20:10:02 UTC

More information about swcEcon at CRAN
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Package PhenotypeR updated to version 0.4.0 with previous version 0.3.4 dated 2026-03-25

Title: Assess Study Cohorts Using a Common Data Model
Description: Phenotype study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model. Diagnostics are run at the database, code list, cohort, and population level to assess whether study cohorts are ready for research.
Author: Edward Burn [aut, cre] , Marti Catala [aut] , Xihang Chen [aut] , Marta Alcalde-Herraiz [aut] , Nuria Mercade-Besora [aut] , Albert Prats-Uribe [aut]
Maintainer: Edward Burn <edward.burn@ndorms.ox.ac.uk>

Diff between PhenotypeR versions 0.3.4 dated 2026-03-25 and 0.4.0 dated 2026-04-16

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Package ieTest updated to version 2.1 with previous version 2.0 dated 2025-04-02

Title: Indirect Effects Testing Methods in Mediation Analysis
Description: Used in testing if the indirect effect from linear regression mediation analysis is equal to 0. Includes established methods such as the Sobel Test, Joint Significant test (maxP), and tests based off the distribution of the Product or Normal Random Variables. Additionally, this package adds more powerful tests based on Intersection-Union theory. These tests are the S-Test, the ps-test, and the ascending squares test. These new methods are uniformly more powerful than maxP, which is more powerful than Sobel and less anti-conservative than the Product of Normal Random Variables. These methods are explored by Kidd and Lin, (2024) <doi:10.1007/s12561-023-09386-6> and Kidd et al., (2025) <doi:10.1007/s10260-024-00777-7>.
Author: John Kidd [aut, cre]
Maintainer: John Kidd <jkidd@uvu.edu>

Diff between ieTest versions 2.0 dated 2025-04-02 and 2.1 dated 2026-04-16

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More information about ieTest at CRAN
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Package ICEHmeasures updated to version 1.1.0 with previous version 1.0.1 dated 2026-03-11

Title: The Equiplot Graph and Complex Inequality Measures
Description: Generates the equiplot, an iconic dot-plot graph for visualizing inequalities, as well as three complex inequality measures: the slope index of inequality, the concentration index and the mean absolute difference to the mean. For more details see World Health Organization (2013) <https://www.who.int/docs/default-source/gho-documents/health-equity/handbook-on-health-inequality-monitoring/handbook-on-health-inequality-monitoring.pdf>.
Author: Leonardo Ferreira [aut, cre], Luisa Arroyave [aut]
Maintainer: Leonardo Ferreira <lferreira@equidade.org>

Diff between ICEHmeasures versions 1.0.1 dated 2026-03-11 and 1.1.0 dated 2026-04-16

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More information about ICEHmeasures at CRAN
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Package vsp updated to version 0.1.4 with previous version 0.1.3 dated 2025-08-20

Title: Vintage Sparse PCA for Semi-Parametric Factor Analysis
Description: Provides fast spectral estimation of latent factors in random dot product graphs using the vsp estimator. Under mild assumptions, the vsp estimator is consistent for (degree-corrected) stochastic blockmodels, (degree-corrected) mixed-membership stochastic blockmodels, and degree-corrected overlapping stochastic blockmodels.
Author: Karl Rohe [aut], Muzhe Zeng [aut], Alex Hayes [aut, cre, cph] , Fan Chen [aut]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

Diff between vsp versions 0.1.3 dated 2025-08-20 and 0.1.4 dated 2026-04-16

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More information about vsp at CRAN
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New package laOpenData with initial version 0.1.0
Package: laOpenData
Title: Convenient Access to Los Angeles Open Data API Endpoints
Version: 0.1.0
Description: Provides simple, reproducible access to datasets from the Los Angeles Open Data portal <https://data.lacity.org/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tibble, jsonlite, httr, janitor, rlang
Suggests: curl, knitr, ggplot2, rmarkdown, testthat (>= 3.0.0), tidyr, vcr (>= 0.6.0), webmockr
URL: https://martinezc1.github.io/laOpenData/, https://github.com/martinezc1/laOpenData
BugReports: https://github.com/martinezc1/laOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-04-13 00:23:48 UTC; christianmartinez
Author: Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-04-16 19:40:08 UTC

More information about laOpenData at CRAN
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Package ggseg updated to version 2.1.1 with previous version 2.1.0 dated 2026-04-03

Title: Plotting Tool for Brain Atlases
Description: Provides a 'ggplot2' geom and position for visualizing brain region data on cortical, subcortical, and white matter tract atlases. Brain atlas geometries are stored as simple features ('sf'), enabling seamless integration with the 'ggplot2' ecosystem including faceting, custom scales, and themes. Mowinckel & Vidal-Piñeiro (2020) <doi:10.1177/2515245920928009>.
Author: Athanasia Mo Mowinckel [aut, cre, cph] , Didac Vidal-Pineiro [aut, cph] , Ramiro Magno [aut] , Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway [cph]
Maintainer: Athanasia Mo Mowinckel <a.m.mowinckel@psykologi.uio.no>

Diff between ggseg versions 2.1.0 dated 2026-04-03 and 2.1.1 dated 2026-04-16

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New package digiNORM with initial version 0.1.0
Package: digiNORM
Title: Data-Driven Digital PCR Normalization
Version: 0.1.0
Description: Adopts the general least squares-based data-driven normalization strategy developed by Heckmann et al. (2011) <doi:10.1186/1471-2105-12-250> to correct for technical variance in gene expression data generated via digital polymerase chain reaction (dPCR). Performs normalization of raw copy numbers and also calculates relative variability metrics that can be used to assess the impact of normalization on variance.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: utils
Suggests: testthat (>= 3.0.0)
Author: Grant C. O'Connell [aut, cre]
Maintainer: Grant C. O'Connell <goconnell.phd@gmail.com>
Repository: CRAN
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-04-12 21:37:04 UTC; gco6
Date/Publication: 2026-04-16 19:40:13 UTC

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New package DecisionDrift with initial version 0.1.0
Package: DecisionDrift
Title: Detecting, Decomposing, and Stress-Testing Temporal Change in Repeated Decision Systems
Version: 0.1.0
Description: Tools for detecting, decomposing, and stress-testing temporal drift in repeated binary decision systems. Complements the 'decisionpaths' package by shifting focus from path construction to system-level change over time. Implements five core analytic modules: (1) prevalence drift — did the overall decision rate change over time?; (2) transition drift — did the probability of switching or persisting change?; (3) entropy and stability trends — did path complexity evolve?; (4) group-differential drift — did the system drift differently across subgroups?; (5) change-point and regime-shift detection — did the system change abruptly after a policy or model update? Additionally provides a robustness module for testing stability of drift conclusions across analytic choices, and a sensitivity module for probing vulnerability to data problems including missingness, miscoding, and threshold shifts. Defines four original drift indices: the Decision Drift Index (DDI), Transition Drift Index (TDI), G [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: cli (>= 3.0.0), rlang (>= 0.4.0), stats, tibble (>= 3.0.0)
Suggests: decisionpaths, ggplot2 (>= 3.3.0), knitr, patchwork, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/causalfragility-lab/DecisionDrift
BugReports: https://github.com/causalfragility-lab/DecisionDrift/issues
NeedsCompilation: no
Packaged: 2026-04-12 22:03:02 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-16 19:42:19 UTC

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New package statAPA with initial version 0.1.0
Package: statAPA
Title: APA 7th Edition Statistical Tables, Plots, and Multilevel Model Reports
Version: 0.1.0
Description: Produces publication-ready statistical tables and figures formatted according to the 7th edition of the American Psychological Association (APA) style guidelines. Supports descriptive statistics, t-tests, z-tests, chi-square tests, Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), two-way ANOVA with simple effects, Multivariate Analysis of Variance (MANOVA), robust and cluster-robust regression using Heteroscedasticity-Consistent (HC) standard errors, post-hoc pairwise comparisons, homoskedasticity and heteroscedasticity diagnostics including the Non-Constant Variance (NCV) test, proportion tests, and multilevel mixed-effects models with intraclass correlation coefficients (ICC) and model-comparison tables. Output can be directed to the console, Microsoft Word (via 'officer' and 'flextable'), or LaTeX. For APA style guidelines see American Psychological Association (2020, ISBN:978-1-4338-3216-1).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats, utils, ggplot2 (>= 3.4.0), rlang, emmeans (>= 1.8.0), lme4 (>= 1.1-30), lmtest (>= 0.9-40), sandwich (>= 3.0-0), car (>= 3.1-0), officer (>= 0.6.0), flextable (>= 0.9.0)
Suggests: lmerTest (>= 3.1-3), MuMIn (>= 1.47.0), ggeffects (>= 1.3.0), knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/causalfragility-lab/statAPA
BugReports: https://github.com/causalfragility-lab/statAPA/issues
NeedsCompilation: no
Packaged: 2026-04-11 19:19:11 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-16 18:30:02 UTC

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New package roroph with initial version 0.1.1
Package: roroph
Title: Philippine Roll-on/Roll-Off (RoRo) Connectivity and Transport Data
Version: 0.1.1
Description: Provides the first standardized dataset of the Philippines' Roll-on/Roll-off (RoRo) shipping network, reflecting the 2024-2026 operational state. It digitizes fragmented records from the Maritime Industry Authority (MARINA) and Philippine Ports Authority (PPA) into a unified framework for transport modeling. The package includes 108 bidirectional provincial links across the Western, Central, and Eastern Nautical Highways, complete with GADM-standardized naming, geospatial coordinates, and metrics such as distance, travel time, and vessel frequency. Methodology follows Anselin (1988, ISBN:9024737354) and LeSage and Pace (2009) <doi:10.1201/9781420064254> for spatial weight construction. Data sources include "MARINA Inventory of RoRo Routes" <https://marina.gov.ph> and "PPA Port Statistics" <https://www.ppa.com.ph/ppa_statistics>. Designed to support research in economic geography and disaster-response logistics.
License: MIT + file LICENSE
URL: https://github.com/njtalingting/roroph
BugReports: https://github.com/njtalingting/roroph/issues
Depends: R (>= 3.5.0)
Imports: ArchipelagoEngine, dplyr, ggplot2, sf, spdep
Suggests: knitr, rmarkdown, rnaturalearth, rnaturalearthdata, ggrepel, ggspatial
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
Language: en-PH
NeedsCompilation: no
Packaged: 2026-04-09 17:16:41 UTC; Nino Jay Talingting
Author: NJ Talingting [aut, cre]
Maintainer: NJ Talingting <ninotalingting77@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 18:20:02 UTC

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Package pressuRe updated to version 0.2.7 with previous version 0.2.5 dated 2025-02-20

Title: Imports, Processes, and Visualizes Biomechanical Pressure Data
Description: Allows biomechanical pressure data from a range of systems to be imported and processed in a reproducible manner. Automatic and manual tools are included to let the user define regions (masks) to be analyzed. Also includes functions for visualizing and animating pressure data. Example methods are described in Shi et al., (2022) <doi:10.1038/s41598-022-19814-0>, Lee et al., (2014) <doi:10.1186/1757-1146-7-18>, van der Zward et al., (2014) <doi:10.1186/1757-1146-7-20>, Najafi et al., (2010) <doi:10.1016/j.gaitpost.2009.09.003>, Cavanagh and Rodgers (1987) <doi:10.1016/0021-9290(87)90255-7>.
Author: Scott Telfer [aut, cre, cph] , Ellen Li [aut]
Maintainer: Scott Telfer <scott.telfer@gmail.com>

Diff between pressuRe versions 0.2.5 dated 2025-02-20 and 0.2.7 dated 2026-04-16

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New package netmem with initial version 1.0-3
Package: netmem
Version: 1.0-3
Date: 2026-04-01
Depends: R (>= 4.0.0)
Imports: igraph, Matrix, stats
Suggests: knitr, rmarkdown, covr, testthat, usethis, styler
Title: Social Network Measures using Matrices
Maintainer: Alejandro Espinosa-Rada <anespinosa@uc.cl>
Description: Provides measures to describe and manipulate one-mode, two-mode, multiplex, and multilevel networks using matrix algebra. Implements functions for network centrality, cohesive subgroups, structural holes, similarity measures, path distances, signed networks, and random network generation. Supports ego-centric and whole-network analyses, including dyadic and triadic census, structural balance, and bipartite projections. Key references: Bonacich (1972) <doi:10.1080/0022250X.1972.9989806>, Breiger (1974) <doi:10.2307/2576011>, Kivelä et al. (2014) <doi:10.1093/comnet/cnu016>, Espinosa-Rada et al. (2024) <doi:10.1016/j.socnet.2023.11.008>.
License: GPL-3
Encoding: UTF-8
Language: en-US
URL: https://github.com/anespinosa/netmem, https://anespinosa.github.io/netmem/
BugReports: https://github.com/anespinosa/netmem/issues
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-04-11 14:50:28 UTC; alejandroespinosa
Author: Alejandro Espinosa-Rada [cre, aut]
Repository: CRAN
Date/Publication: 2026-04-16 18:20:11 UTC

More information about netmem at CRAN
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Package mrf readmission to version 0.1.9 with previous version 0.1.6 dated 2022-02-23

Title: Multiresolution Forecasting
Description: Forecasting of univariate time series using feature extraction with variable prediction methods is provided. Feature extraction is done with a redundant Haar wavelet transform with filter h = (0.5, 0.5). The advantage of the approach compared to typical Fourier based methods is an dynamic adaptation to varying seasonalities. Currently implemented prediction methods based on the selected wavelets levels and scales are a regression and a multi-layer perceptron. Forecasts can be computed for horizon 1 or higher. Model selection is performed with an evolutionary optimization. Selection criteria are currently the AIC criterion, the Mean Absolute Error or the Mean Root Error. The data is split into three parts for model selection: Training, test, and evaluation dataset. The training data is for computing the weights of a parameter set. The test data is for choosing the best parameter set. The evaluation data is for assessing the forecast performance of the best parameter set on new data unkn [...truncated...]
Author: Quirin Stier [aut, cre, ctb] , Michael Thrun [ths, cph, rev, fnd, ctb]
Maintainer: Quirin Stier <research@quirin-stier.de>

This is a re-admission after prior archival of version 0.1.6 dated 2022-02-23

Diff between mrf versions 0.1.6 dated 2022-02-23 and 0.1.9 dated 2026-04-16

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More information about mrf at CRAN
Permanent link

New package linreg with initial version 0.1.0
Package: linreg
Title: Linear Regression and Model Selection Framework
Version: 0.1.0
Author: Dr. Pramit Pandit [aut, cre], Dr. Bikramjeet Ghose [aut], Dr. Chiranjit Mazumder [aut]
Maintainer: Dr. Pramit Pandit <pramitpandit@gmail.com>
Description: Provides a comprehensive framework for linear regression modeling and associated statistical analysis. The package implements methods for correlation analysis, including computation of correlation matrices with corresponding significance levels and visualization via correlation heatmaps. It supports estimation of multiple linear regression models, along with automated model selection through backward elimination procedures based on statistical significance criteria. In addition, the package offers a suite of diagnostic tools to assess key assumptions of linear regression, including multicollinearity using variance inflation factors, heteroscedasticity using the Goldfeld-Quandt test, and normality of residuals using the Shapiro-Wilk test. These functionalities, as described in Draper and Smith (1998) <doi:10.1002/9781118625590>, are designed to facilitate robust model building, evaluation, and interpretation in applied statistical and data analytical contexts.
License: GPL-3
Encoding: UTF-8
Imports: stats, Hmisc, corrplot, car, lmtest
NeedsCompilation: no
Packaged: 2026-04-11 14:05:51 UTC; prami
Repository: CRAN
Date/Publication: 2026-04-16 18:20:18 UTC

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New package gleam with initial version 0.8.0
Package: gleam
Title: Global Livestock Environmental Assessment Model (GLEAM-X)
Version: 0.8.0
Description: The official implementation of the Global Livestock Environmental Assessment Model (GLEAM) of the Food and Agriculture Organization of the United Nations (FAO) in R. GLEAM-X provides a modular, transparent framework for simulating livestock production systems and quantifying their environmental impacts. Methodological background: MacLeod et al. (2017) "Invited review: A position on the Global Livestock Environmental Assessment Model (GLEAM)" <doi:10.1017/S1751731117001847>. Further information: <https://www.fao.org/gleam/en/>.
License: AGPL-3
URL: https://github.com/un-fao/GLEAM/, https://www.fao.org/gleam/en/
BugReports: https://github.com/un-fao/GLEAM/issues
Encoding: UTF-8
Imports: cli (>= 3.0.0), data.table (>= 1.16.0)
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
VignetteBuilder: knitr
Depends: R (>= 4.4.0)
NeedsCompilation: no
Packaged: 2026-04-11 15:10:06 UTC; ahmed
Author: Ahmed Jou [aut, cre] , Yassine Elaouni [aut] , Dominik Wisser [aut] , Lydia Lanzoni [aut] , Giuseppe Tempio [aut] , Phyllis Ndungu' [ctb] , Yushan Li [ctb] , Manling Xu [ctb] , Zixin Wang [ctb] , Narindra Rakotovao [ctb] , Stewart Chikoloma [ctb] , D [...truncated...]
Maintainer: Ahmed Jou <ahmed@applitics.fr>
Repository: CRAN
Date/Publication: 2026-04-16 18:30:08 UTC

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Package neuroim2 updated to version 0.13.0 with previous version 0.8.5 dated 2026-01-14

Title: Data Structures for Brain Imaging Data
Description: A collection of data structures and methods for handling volumetric brain imaging data, with a focus on functional magnetic resonance imaging (fMRI). Provides efficient representations for three-dimensional and four-dimensional neuroimaging data through sparse and dense array implementations, memory-mapped file access for large datasets, and spatial transformation capabilities. Implements methods for image resampling, spatial filtering, region of interest analysis, and connected component labeling. General introduction to fMRI analysis can be found in Poldrack et al. (2024, "Handbook of functional MRI data analysis", <ISBN:9781108795760>).
Author: Bradley R Buchsbaum [aut, cre, cph]
Maintainer: Bradley R Buchsbaum <brad.buchsbaum@gmail.com>

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Package geneticae updated to version 1.0.0 with previous version 0.4.0 dated 2022-07-20

Title: Statistical Tools for the Analysis of Multi Environment Agronomic Trials
Description: Data from multi environment agronomic trials, which are often carried out by plant breeders, can be analyzed with the tools offered by this package such as the Additive Main effects and Multiplicative Interaction model or 'AMMI' ('Gauch' 1992, ISBN:9780444892409) and the Site Regression model or 'SREG' ('Cornelius' 1996, <doi:10.1201/9780367802226>). Since these methods present a poor performance under the presence of outliers and missing values, this package includes robust versions of the 'AMMI' model ('Rodrigues' 2016, <doi:10.1093/bioinformatics/btv533>), and also imputation techniques specifically developed for this kind of data ('Arciniegas-Alarcón' 2014, <doi:10.2478/bile-2014-0006>).
Author: Julia Angelini [aut, cre] , Marcos Prunello [aut] , Gerardo Cervigni [aut]
Maintainer: Julia Angelini <jangelini_93@hotmail.com>

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Package devtools updated to version 2.5.1 with previous version 2.5.0 dated 2026-03-14

Title: Tools to Make Developing R Packages Easier
Description: Collection of package development tools.
Author: Hadley Wickham [aut], Jim Hester [aut], Winston Chang [aut], Jennifer Bryan [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Jennifer Bryan <jenny@posit.co>

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Package TestGenerator updated to version 0.6.0 with previous version 0.5.0 dated 2026-01-14

Title: Integration Unit Tests for Pharmacoepidemiological Studies
Description: An R interface to load testing data in the 'OMOP' Common Data Model ('CDM'). An input file, csv or xlsx, can be converted to a 'CDMConnector' object. This object can be used to execute and test studies that use the 'CDM' <https://www.ohdsi.org/data-standardization/>.
Author: Cesar Barboza [aut] , Ioanna Nika [aut], Ger Inberg [aut, cre] , Adam Black [aut]
Maintainer: Ger Inberg <g.inberg@erasmusmc.nl>

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Package fairmetrics updated to version 1.0.8 with previous version 1.0.7 dated 2025-10-06

Title: Fairness Evaluation Metrics with Confidence Intervals for Binary Protected Attributes
Description: A collection of functions for computing fairness metrics for machine learning and statistical models, including confidence intervals for each metric. The package supports the evaluation of group-level fairness criterion commonly used in fairness research, particularly in healthcare for binary protected attributes. It is based on the overview of fairness in machine learning written by Gao et al (2025) <doi:10.1002/sim.70234>.
Author: Jianhui Gao [aut] , Benjamin Smith [aut, cre] , Benson Chou [aut] , Jessica Gronsbell [aut]
Maintainer: Benjamin Smith <benyamin.smith@mail.utoronto.ca>

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Package rgoogleads updated to version 0.14.1 with previous version 0.13.3 dated 2025-09-03

Title: Loading Data from 'Google Ads API'
Description: Interface for loading data from 'Google Ads API', see <https://developers.google.com/google-ads/api/docs/start>. Package provide function for authorization and loading reports.
Author: Alexey Seleznev [aut, cre] , Netpeak [cph]
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package test.assessr updated to version 2.0.0 with previous version 1.1.1 dated 2026-03-02

Title: Assessing Package Test Reliability and Quality
Description: A reliable and validated tool that calculates unit test coverage for R packages with standard testing frameworks and non-standard testing frameworks.
Author: Edward Gillian [cre, aut] , Hugo Bottois [aut] , Paulin Charliquart [aut], Andre Couturier [aut], Sanofi [cph, fnd]
Maintainer: Edward Gillian <edward.gillian-ext@sanofi.com>

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New package llm.api with initial version 0.1.1
Package: llm.api
Title: Minimal LLM Chat Interface
Version: 0.1.1
Description: A minimal-dependency client for Large Language Model chat APIs. Supports 'OpenAI' <https://github.com/openai>, 'Anthropic' 'Claude' <https://claude.com/>, 'Moonshot' 'Kimi' <https://www.moonshot.ai/>, 'Ollama' <https://ollama.com/>, and other 'OpenAI'-compatible endpoints. Includes an agent loop with tool use and a 'Model Context Protocol' client <https://modelcontextprotocol.io/>. API design is derived from the 'ellmer' package, reimplemented with only base R, 'curl', and 'jsonlite'.
License: MIT + file LICENSE
URL: https://github.com/cornball-ai/llm.api
BugReports: https://github.com/cornball-ai/llm.api/issues
Encoding: UTF-8
Imports: curl, jsonlite
Suggests: tinytest
NeedsCompilation: no
Packaged: 2026-04-11 01:53:52 UTC; troy
Author: Troy Hernandez [aut, cre] , ellmer team [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-04-16 11:00:02 UTC

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New package xiacf with initial version 0.4.0
Package: xiacf
Title: Quantifying Nonlinear Dependence and Lead-Lag Dynamics via Chatterjee's Xi
Version: 0.4.0
Maintainer: Yasunori Watanabe <watanabe.yasunori@outlook.com>
Description: Computes Chatterjee's non-parametric correlation coefficient for time series data. It extends the original metric to time series analysis by providing the Xi-Autocorrelation Function (Xi-ACF) and Xi-Cross-Correlation Function (Xi-CCF). The package allows users to test for non-linear dependence using Iterative Amplitude Adjusted Fourier Transform (IAAFT) surrogate data. Main functions include xi_acf() and xi_ccf() for computation, along with matrix extraction tools. Methodologies are based on Chatterjee (2021) <doi:10.1080/01621459.2020.1758115> and surrogate data testing methods by Schreiber and Schmitz (1996) <doi:10.1103/PhysRevLett.77.635>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr (>= 1.1.4), doFuture, foreach, future, ggplot2 (>= 4.0.1), latex2exp, progressr, Rcpp (>= 1.1.0), stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.3.2)
NeedsCompilation: yes
Packaged: 2026-04-10 18:54:56 UTC; yasunori
Author: Yasunori Watanabe [aut, cre]
Repository: CRAN
Date/Publication: 2026-04-16 10:40:02 UTC

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New package SamsaRaLight with initial version 1.0.0
Package: SamsaRaLight
Title: Simulate Tree Light Transmission Using Ray-Tracing
Version: 1.0.0
Description: Provides tools to simulate light transmission in forest stands using three-dimensional ray-tracing. The package allows users to build virtual stands from tree inventories and to estimate (1) light intercepted by individual trees, (2) light reaching the forest floor, and (3) light at virtual sensors. The package is designed for ecological and forestry applications, including the analysis of light competition, tree growth, and forest regeneration. The implementation builds on the individual-based ray-tracing model SamsaraLight developed by Courbaud et al. (2003) <doi:10.1016/S0168-1923(02)00254-X>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: concaveman, data.table, dplyr, ggforce, ggnewscale, ggplot2, grid, httr, patchwork, Rcpp, RhpcBLASctl, scales, sf, sfheaders, tidyr
LinkingTo: Rcpp
LazyData: true
Suggests: cowplot, knitr, purrr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://natheob.github.io/SamsaRaLight/
BugReports: https://github.com/natheob/SamsaRaLight/issues/
NeedsCompilation: yes
Packaged: 2026-04-10 13:03:26 UTC; Nathéo Beauchamp
Author: Natheo Beauchamp [aut, cre] , Gauthier Ligot [aut] , Francois de Coligny [aut] , Maxime Jaunatre [aut] , Benoit Courbaud [aut, cph]
Maintainer: Natheo Beauchamp <beauchamp.natheo@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 10:12:16 UTC

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New package rquiz with initial version 1.0.0
Package: rquiz
Title: Interactive Quizzes as HTML Widgets
Version: 1.0.0
Description: Creates interactive JavaScript-based quizzes as 'HTML' widgets. Offers three quiz types: a single question with instant feedback (singleQuestion()), a multi-question quiz with navigation, timer, and results (multiQuestions()), and fill-in-the-blank cloze exercises (fillBlanks()). All quizzes auto-detect single-choice and multiple-choice modes from the input data, support customizable styling, keyboard navigation, and multilingual UI (English, German, French, Spanish). Designed for use in 'R Markdown', 'Quarto', and 'Shiny' applications. The singleQuestion() quiz design was inspired by Ozzie Kirkby <https://codepen.io/ozzie/pen/pvrVLm>. The multiQuestions() quiz design was inspired by Abhilash Narayan <https://codepen.io/abhilashn/pen/BRepQz>.
URL: https://github.com/saskiaotto/rquiz, https://saskiaotto.github.io/rquiz/
BugReports: https://github.com/saskiaotto/rquiz/issues
VignetteBuilder: knitr
License: MIT + file LICENSE
Language: en-US
Depends: R (>= 4.1.0)
Imports: htmlwidgets (>= 1.5.0), jsonlite (>= 1.7.0)
Suggests: knitr, rmarkdown, shiny, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-04-10 16:34:49 UTC; saskiaotto
Author: Saskia Otto [aut, cre]
Maintainer: Saskia Otto <saskia.a.otto@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 10:20:03 UTC

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New package rqualify with initial version 1.0.2
Package: rqualify
Title: Qualification of R Software Installations
Version: 1.0.2
Description: Qualify R software installations using R Markdown as the foundation for the Installation Qualification (IQ) and Operational Qualification (OQ) when used in environments (such as regulated clinical trials) where such processes may be required.
License: GPL-2
URL: https://github.com/Medtronic-Biostatistics/rqualify, https://medtronic-biostatistics.github.io/rqualify/
BugReports: https://github.com/Medtronic-Biostatistics/rqualify/issues
Depends: R (>= 4.4.0)
Imports: pandoc, rmarkdown, tinytex
Suggests: knitr, testthat (>= 3.0.0)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-10 13:38:49 UTC; musgrd1
Author: Donnie Musgrove [aut, cre], Graeme L. Hickey [aut] , Marc Schwartz [aut] , Medtronic Inc. [cph]
Maintainer: Donnie Musgrove <donniemusgrove@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 10:10:02 UTC

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Package miniCRAN updated to version 0.3.2 with previous version 0.3.1 dated 2025-04-23

Title: Create a Mini Version of CRAN Containing Only Selected Packages
Description: Makes it possible to create an internally consistent repository consisting of selected packages from CRAN-like repositories. The user specifies a set of desired packages, and 'miniCRAN' recursively reads the dependency tree for these packages, then downloads only this subset. The user can then install packages from this repository directly, rather than from CRAN. This is useful in production settings, e.g. server behind a firewall, or remote locations with slow (or zero) Internet access.
Author: Andrie de Vries [aut, cre, cph], Alex Chubaty [ctb], Microsoft Corporation [cph]
Maintainer: Andrie de Vries <apdevries@gmail.com>

Diff between miniCRAN versions 0.3.1 dated 2025-04-23 and 0.3.2 dated 2026-04-16

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New package hlmLab with initial version 0.1.0
Package: hlmLab
Title: Hierarchical Linear Modeling with Visualization and Decomposition
Version: 0.1.0
Description: Provides functions for visualization and decomposition in hierarchical linear models (HLM) for applications in education, psychology, and the social sciences. Includes variance decomposition for two-level and three-level data structures following Snijders and Bosker (2012, ISBN:9781849202015), intraclass correlation (ICC) estimation and design effect computation as described in Shrout and Fleiss (1979) <doi:10.1037/0033-2909.86.2.420>, and contextual effect decomposition via the Mundlak (1978) <doi:10.2307/1913646> specification distinguishing within- and between-cluster components. Supports visualization of random slopes and cross-level interactions following Hofmann and Gavin (1998) <doi:10.1177/014920639802400504> and Hamaker and Muthen (2020) <doi:10.1037/met0000239>. Multilevel models are estimated using 'lme4' (Bates et al., 2015 <doi:10.18637/jss.v067.i01>). An optional 'Shiny' application enables interactive exploration of model components and para [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2 (>= 3.4.0), lme4, scales, stats
Suggests: shiny, spelling, testthat (>= 3.0.0)
URL: https://github.com/causalfragility-lab/hlmLab
BugReports: https://github.com/causalfragility-lab/hlmLab/issues
NeedsCompilation: no
Packaged: 2026-04-10 20:02:12 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-16 10:50:02 UTC

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New package carsAlgo with initial version 0.5.0
Package: carsAlgo
Title: Competitive Adaptive Reweighted Sampling (CARS) Algorithm
Version: 0.5.0
Maintainer: Md. Ashraful Haque <ashrafulhaque664@gmail.com>
Description: Implements Competitive Adaptive Reweighted Sampling (CARS) algorithm for variable selection from high-dimensional dataset using Partial Least Squares (PLS) regression models. CARS algorithm iteratively applies the Monte Carlo sub-sampling and exponential variable elimination techniques to identify/select the most informative variables/features subjected to minimal cross-validated RMSE score. The implementation of CARS algorithm is inspired from the work of Li et al. (2009) <doi:10.1016/j.aca.2009.06.046>. This algorithm is widely applied in near-infrared (NIR), mid-infrared (MIR), hyperspectral chemometrics areas, etc.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2, pls, rlang, stats, utils
URL: https://github.com/mah-iasri/carsAlgo
BugReports: https://github.com/mah-iasri/carsAlgo/issues
NeedsCompilation: no
Packaged: 2026-04-10 13:44:44 UTC; Ashraful
Author: Md. Ashraful Haque [aut, cre], Avijit Ghosh [aut], Sayantani Karmakar [aut], Harsh Sachan [aut], Shalini Kumari [aut]
Repository: CRAN
Date/Publication: 2026-04-16 10:12:11 UTC

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Package bayesRecon updated to version 1.0.1 with previous version 1.0.0 dated 2026-03-07

Title: Probabilistic Reconciliation via Conditioning
Description: Provides methods for probabilistic reconciliation of hierarchical forecasts of time series. The available methods include analytical Gaussian reconciliation (Corani et al., 2021) <doi:10.1007/978-3-030-67664-3_13>, MCMC reconciliation of count time series (Corani et al., 2024) <doi:10.1016/j.ijforecast.2023.04.003>, Bottom-Up Importance Sampling (Zambon et al., 2024) <doi:10.1007/s11222-023-10343-y>, methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) (Zambon et al., 2024) <https://proceedings.mlr.press/v244/zambon24a.html>, analytical reconciliation with Bayesian treatment of the covariance matrix (Carrara et al., 2025) <doi: 10.48550/arXiv.2506.19554>.
Author: Dario Azzimonti [aut, cre] , Lorenzo Zambon [aut] , Stefano Damato [aut] , Nicolo Rubattu [aut] , Giorgio Corani [aut]
Maintainer: Dario Azzimonti <dario.azzimonti@gmail.com>

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 bayesRecon-1.0.1/bayesRecon/R/PMF.R                                                                          |    7 
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 bayesRecon-1.0.1/bayesRecon/tests/testthat/test-PMF.R                                                        |   15 
 bayesRecon-1.0.1/bayesRecon/tests/testthat/test-reconc_BUIS_gaussian.R                                       |   20 
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New package spmixW with initial version 0.2.2
Package: spmixW
Title: Bayesian Spatial Panel Data Models with Convex Combinations of Weight Matrices
Version: 0.2.2
Description: Bayesian Markov chain Monte Carlo (MCMC) estimation of spatial panel data models including Spatial Autoregressive (SAR), Spatial Durbin Model (SDM), Spatial Error Model (SEM), Spatial Durbin Error Model (SDEM), and Spatial Lag of X (SLX) specifications with fixed effects. Supports convex combinations of multiple spatial weight matrices and Bayesian Model Averaging (BMA) over subsets of weight matrices. Implements the convex combination spatial weight matrix methodology of Debarsy and LeSage (2021) <doi:10.1080/07350015.2020.1840993> and the Bayesian spatial panel data models of LeSage and Pace (2009, ISBN:9781420064247).
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: Matrix, MASS, coda
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spdep, sf, ggplot2, broom
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-04-09 18:17:38 UTC; musta
Author: Mustapha Wasseja Mohammed [aut, cre]
Maintainer: Mustapha Wasseja Mohammed <muswaseja@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 09:20:02 UTC

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New package RobustMediate with initial version 0.1.1
Package: RobustMediate
Title: Causal Mediation Analysis with Diagnostics and Sensitivity Analysis
Version: 0.1.1
Description: Provides tools for causal mediation analysis with continuous treatments using inverse probability weighting (IPW). Estimates natural direct and indirect effects over a user-defined treatment grid and supports flexible dose-response mediation analysis. Includes diagnostic procedures for assessing covariate balance in both treatment and mediator models using standardized mean differences. Implements pathway-specific extensions of the impact threshold for a confounding variable (ITCV; Frank, 2000 <doi:10.1177/0049124100029002001>) adapted to mediation settings. Provides joint sensitivity analysis combining E-values (VanderWeele and Ding, 2017 <doi:10.7326/M16-2607>) and violations of sequential ignorability (Imai, Keele, and Yamamoto, 2010 <doi:10.1214/10-STS321>). Additional utilities include visualization of dose-response mediation functions, robustness profiles, fragility summaries, and formatted outputs for applied research. Supports clustered data structures and mul [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/causalfragility-lab/RobustMediate
BugReports: https://github.com/causalfragility-lab/RobustMediate/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: cli, ggplot2 (>= 3.4.0), rlang, scales, stats, broom
Suggests: covr, dplyr, knitr, lme4, pkgdown, rmarkdown, splines, testthat (>= 3.0.0), tidyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-09 16:50:37 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-16 09:12:11 UTC

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New package munch with initial version 0.0.2
Package: munch
Title: Rich Inline Text for 'grid' Graphics and 'flextable'
Version: 0.0.2
Description: Renders rich inline text (bold, italic, code, links, images) in grid graphics and 'ggplot2', from markdown or 'flextable' chunks. Provides grobs, theme elements, and geometry layers for styled text rendering. Only works with graphics devices that support 'systemfonts', such as those provided by 'ragg', 'svglite', or 'ggiraph'. The 'cairo_pdf' device is also supported when fonts are installed at the system level.
License: MIT + file LICENSE
URL: https://ardata-fr.github.io/munch/
BugReports: https://github.com/ardata-fr/munch/issues
Imports: cli, commonmark, flextable, patchwork, gdtools, ggplot2, grid, methods, systemfonts, xml2
Suggests: doconv, ggiraph, knitr, magick, ragg, rmarkdown, rsvg, svglite, testthat (>= 3.0.0), withr
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-04-09 09:48:14 UTC; davidgohel
Author: David Gohel [aut, cre], ArData [cph]
Maintainer: David Gohel <david.gohel@ardata.fr>
Repository: CRAN
Date/Publication: 2026-04-16 09:10:02 UTC

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New package GWnorm with initial version 1.0
Package: GWnorm
Title: G-Wishart Normalising Constants for Gaussian Graphical Models
Version: 1.0
Date: 2026-03-26
Author: Ching Wong [aut], Jack Kuipers [aut, cre]
Maintainer: Jack Kuipers <jack.kuipers@bsse.ethz.ch>
Description: Computes G-Wishart normalising constants through a Fourier approach. Either exact analytical results, numerical integration or Monte Carlo estimation are employed. Details at C. Wong, G. Moffa and J. Kuipers (2024), <doi:10.48550/arXiv.2404.06803>.
License: GPL (>= 2)
Depends: R (>= 4.0.0)
Imports: igraph, BDgraph, CholWishart, MASS, mvtnorm, Rcpp (>= 1.1.1)
LinkingTo: Rcpp, RcppEigen
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-04-10 09:22:10 UTC; jkuipers
Repository: CRAN
Date/Publication: 2026-04-16 09:42:03 UTC

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New package glm4 with initial version 0.1.0
Package: glm4
Title: Fitting Generalized Linear Models Using Sparse Matrices
Version: 0.1.0
Description: Fits Generalised Linear Models (GLMs) with sparse and dense 'Matrix' matrices for memory efficiency. Acts as a wrapper for the glm4() function in the 'MatrixModels' package <doi:10.32614/CRAN.package.MatrixModels>, but adds convenient model methods and functions designed to mimic those associated with the glm() function from the 'stats' package.
URL: https://github.com/awhug/glm4/issues
BugReports: https://github.com/awhug/glm4/issues
License: GPL (>= 2)
Encoding: UTF-8
Imports: methods, Matrix, MatrixModels, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-09 23:40:09 UTC; angus
Author: Angus Hughes [aut, cre, cph]
Maintainer: Angus Hughes <angus-hughes+glm4@outlook.com>
Repository: CRAN
Date/Publication: 2026-04-16 09:30:02 UTC

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New package CohortContrast with initial version 1.0.0
Package: CohortContrast
Title: Enrichment Analysis of Clinically Relevant Concepts in Common Data Model Cohort Data
Version: 1.0.0
Maintainer: Markus Haug <markus.haug@ut.ee>
Description: Identifies clinically relevant concepts in Observational Medical Outcomes Partnership Common Data Model cohorts using an enrichment-based workflow. Defines target and control cohorts and extracts medical interventions that are over-represented in the target cohort during the observation period. Users can tune filtering and selection thresholds. The workflow includes chi-squared tests for two proportions with Yates continuity correction, logistic tests, and hierarchy and correlation mappings for relevant concepts. The results can be optionally explored using the bundled graphical user interface. For workflow details and examples, see <https://healthinformaticsut.github.io/CohortContrast/>.
License: Apache License 2.0
Encoding: UTF-8
SystemRequirements: Python (>= 3.8)
Imports: dplyr (>= 1.0.4), tibble, purrr, tidyr (>= 1.0.0), stringr, stats, utils, CDMConnector (>= 2.0.0), CohortConstructor (>= 0.6.0), omopgenerics (>= 1.3.0), lubridate (>= 1.9.0), doParallel, parallel, foreach, data.table (>= 1.14.0), cli, jsonlite (>= 1.8.0), nanoparquet (>= 0.4.0)
Suggests: testthat (>= 3.0.0), PatientProfiles (>= 1.1.0), duckdb, DBI (>= 1.2.0), RPostgres, readr, knitr, rmarkdown, processx, bit64, reshape2, igraph, Matrix, cluster, vegan, reticulate (>= 1.26)
URL: https://healthinformaticsut.github.io/CohortContrast/
BugReports: https://github.com/HealthInformaticsUT/CohortContrast/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-09 14:28:29 UTC; markushaug
Author: Markus Haug [aut, cre] , Raivo Kolde [aut]
Repository: CRAN
Date/Publication: 2026-04-16 09:12:17 UTC

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New package chiOpenData with initial version 0.1.0
Package: chiOpenData
Title: Convenient Access to Chicago Open Data API Endpoints
Version: 0.1.0
Description: Provides simple, reproducible access to datasets from the Chicago Open Data portal <https://data.cityofchicago.org/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tibble, jsonlite, httr, janitor, rlang
Suggests: curl, knitr, ggplot2
URL: https://martinezc1.github.io/chiOpenData/, https://github.com/martinezc1/chiOpenData
BugReports: https://github.com/martinezc1/chiOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-04-09 17:56:05 UTC; christianmartinez
Author: Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-04-16 09:22:11 UTC

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New package APS with initial version 1.0.1
Package: APS
Title: Analysing Prediction Stability of Non-Deterministic Prediction Models
Version: 1.0.1
Maintainer: Thomas Martin Lange <thomas.lange@uni-goettingen.de>
Description: Provides methods to analyse the stability of non-deterministic prediction models. Prediction stability is quantified either as data-based prediction stability (phi) or as model-based prediction stability (psi). The package implements measures for categorical, ordinal, and metric predictions based on repeated model fitting and corresponding predictions. Methods are based on Lange et al. (2025) <doi:10.1186/s12859-025-06097-1>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: stats
Suggests: ranger, covr, rmarkdown, spelling, testthat
NeedsCompilation: no
Packaged: 2026-04-09 12:25:10 UTC; thoma
Author: Thomas Martin Lange [cre, aut] , Felix Heinrich [ctb]
LazyData: true
Repository: CRAN
Date/Publication: 2026-04-16 09:02:07 UTC

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New package senatebR with initial version 0.1.0
Package: senatebR
Title: Collect Data from the Brazilian Federal Senate Open Data API
Version: 0.1.0
Description: Provides functions to access and collect data from the Brazilian Federal Senate open data API and website. Covers senators, legislative materials, committees, voting records, speeches, provisional measures, vetoes, and legislative agendas, returning results as tidy data frames ready for analysis.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: glue (>= 1.6.2), lubridate (>= 1.9.3), jsonlite (>= 1.8.8), xml2 (>= 1.3.6), magrittr (>= 2.0.3), httr (>= 1.4.7), rvest (>= 1.0.0), dplyr (>= 1.1.2), tidyr (>= 1.3.0), purrr (>= 1.0.2), stringr (>= 1.5.1)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr, ggplot2
VignetteBuilder: knitr
URL: https://github.com/vsntos/senatebR
BugReports: https://github.com/vsntos/senatebR/issues
NeedsCompilation: no
Packaged: 2026-04-08 21:56:22 UTC; viniciussantos
Author: Vinicius Santos [aut, cre]
Maintainer: Vinicius Santos <santos.vinicius18@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 08:40:02 UTC

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New package nowcastr with initial version 0.2.0
Version: 0.2.0
Package: nowcastr
Title: Nowcasting with Chain-Ladder Method
Description: Tools for performing nowcasting using the Chain-Ladder method <https://en.wikipedia.org/wiki/Chain-ladder_method>. It supports both non-cumulative delay-based estimation and model-based completeness fitting (e.g., using logistic or Gompertz curves) to predict final counts from partially reported data.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: S7, rlang, magrittr, dplyr, tidyr, stats, purrr, ggplot2, scales, cli
Depends: R (>= 4.1.0)
Suggests: ISOweek, testthat (>= 3.0.0), quarto, shiny, bslib, DT
VignetteBuilder: quarto
URL: https://github.com/whocov/nowcastr, https://whocov.github.io/nowcastr/
BugReports: https://github.com/whocov/nowcastr/issues
NeedsCompilation: no
Packaged: 2026-04-09 07:33:29 UTC; mleroy
Author: Mathias Leroy [aut, cre], Finlay Campbell [aut]
Maintainer: Mathias Leroy <mathias.leroy.rpkg@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 08:30:02 UTC

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New package emBALVI with initial version 0.1.0
Package: emBALVI
Title: EM Bayesian Adaptive LASSO Variational Inference Based GWAS
Version: 0.1.0
Description: Performs Genome-Wide Association Study (GWAS) analysis using Expectation-Maximization Bayesian Adaptive LASSO with Variational Inference (emBALVI). Includes genotype preprocessing, genomic relationship matrix construction, GWAS analysis, Manhattan and QQ plotting.s.
Depends: R (>= 4.0)
Imports: ggplot2, RColorBrewer
Suggests: rmarkdown, testthat (>= 3.0.0), roxygen2
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-04-09 09:49:46 UTC; iasri
Author: Prakash Kumar [aut, cre], Himadri Sekhar Roy [aut], Ranjit Kumar Paul [aut], Md. Yeasin [aut], Neeraj Budhlakoti [aut], Sunil Kumar Yadav [aut], Amrit Kumar Paul [aut]
Maintainer: Prakash Kumar <prakash289111@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-16 08:30:08 UTC

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Package salso updated to version 0.3.78 with previous version 0.3.77 dated 2026-04-12

Title: Search Algorithms and Loss Functions for Bayesian Clustering
Description: The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.
Author: David B. Dahl [aut, cre] , Devin J. Johnson [aut] , Peter Mueller [aut], Andres Felipe Barrientos [aut], Garritt Page [aut], David Dunson [aut], Authors of the dependency Rust crates [ctb]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between salso versions 0.3.77 dated 2026-04-12 and 0.3.78 dated 2026-04-16

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Package salmonMSE updated to version 2.0.0 with previous version 1.0.0 dated 2026-03-20

Title: Management Strategy Evaluation for Salmon Species
Description: Simulation tools to evaluate the long-term effects of salmon management strategies, including a combination of habitat, harvest, and habitat actions. The stochastic age-structured operating model accommodates complex life histories, including freshwater survival across early life stages, juvenile survival and fishery exploitation in the marine life stage, partial maturity by age class, and fitness impacts of hatchery programs on natural spawning populations. 'salmonMSE' also provides an age-structured conditioning model to develop operating models fitted to data.
Author: Quang Huynh [aut, cre]
Maintainer: Quang Huynh <quang@bluematterscience.com>

Diff between salmonMSE versions 1.0.0 dated 2026-03-20 and 2.0.0 dated 2026-04-16

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Package rockchalk updated to version 1.8.164 with previous version 1.8.157 dated 2022-08-06

Title: Regression Estimation and Presentation
Description: A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <https://pj.freefaculty.org/guides/>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.
Author: Paul E. Johnson [aut, cre], Gabor Grothendieck [ctb], Dimitri Papadopoulos OrfanosGabor [ctb]
Maintainer: Paul E. Johnson <pauljohn32@freefaculty.org>

Diff between rockchalk versions 1.8.157 dated 2022-08-06 and 1.8.164 dated 2026-04-16

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Package renv updated to version 1.2.2 with previous version 1.2.1 dated 2026-04-12

Title: Project Environments
Description: A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.
Author: Kevin Ushey [aut, cre] , Hadley Wickham [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Kevin Ushey <kevin@rstudio.com>

Diff between renv versions 1.2.1 dated 2026-04-12 and 1.2.2 dated 2026-04-16

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Package ReliaGrowR updated to version 0.6 with previous version 0.4 dated 2026-03-31

Title: Reliability Growth Analysis and Repairable Systems Modeling
Description: Modeling and plotting functions for Reliability Growth Analysis (RGA) and Non-Homogeneous Poisson Process (NHPP) models for repairable systems. RGA models include the Duane (1962) <doi:10.1109/TA.1964.4319640>, NHPP by Crow (1975) (No. AMSAATR138), Piecewise Weibull NHPP by Guo et al. (2010) <doi:10.1109/RAMS.2010.5448029>, and Piecewise Weibull NHPP with Change Point Detection based on the 'segmented' package by Muggeo (2024) <https://cran.r-project.org/package=segmented>. Repairable systems functions include the Mean Cumulative Function (MCF) using the Nelson-Aalen estimator, parametric Power Law and Log-Linear NHPP models, and forecasting.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

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Package phylospatial updated to version 1.4.0 with previous version 1.3.0 dated 2026-04-03

Title: Spatial Phylogenetic Analysis
Description: Analyze spatial phylogenetic diversity patterns. Use your data on an evolutionary tree and geographic distributions of the terminal taxa to compute diversity and endemism metrics, test significance with null model randomization, analyze community turnover and biotic regionalization, and perform spatial conservation prioritizations. All functions support quantitative community data in addition to binary data.
Author: Matthew Kling [aut, cre, cph]
Maintainer: Matthew Kling <mattkling@berkeley.edu>

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Package MultiSpline updated to version 0.2.0 with previous version 0.1.1 dated 2026-03-16

Title: Spline-Based Nonlinear Modeling for Multilevel and Longitudinal Data
Description: Provides a unified framework for fitting, predicting, and interpreting nonlinear relationships in single-level, multilevel, and longitudinal regression models. Flexible functional forms are supported using natural cubic splines ('splines'), B-splines ('splines'), and GAM smooths ('mgcv'). Supports two-way and nested clustering via 'lme4', automatic knot selection by AIC or BIC, multilevel R-squared decomposition (Nakagawa-Schielzeth marginal and conditional R-squared with level-specific variance partitioning), a postestimation suite returning first and second derivatives with confidence bands, turning points and inflection regions, and a model comparison workflow contrasting linear, polynomial, and spline fits by AIC, BIC, and likelihood-ratio tests. Cluster heterogeneity in nonlinear effects is supported via random-slope spline terms.
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>

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Package motmot readmission to version 2.1.4 with previous version 2.1.3 dated 2019-11-25

Title: Models of Trait Macroevolution on Trees
Description: Functions for fitting models of trait evolution on phylogenies for continuous traits. The majority of functions are described in Thomas and Freckleton (2012) <doi:10.1111/j.2041-210X.2011.00132.x> and allow tests of variation in the rates of trait evolution.
Author: Mark Puttick [aut, cph] , Gavin Thomas [aut, cph], Rob Freckleton [aut, cph], Magnus Clarke [ctb], Travis Ingram [ctb], David Orme [ctb], Emmanuel Paradis [ctb], Martin R. Smith [ctb, cre]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

This is a re-admission after prior archival of version 2.1.3 dated 2019-11-25

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Package BREADR updated to version 1.1.0 with previous version 1.0.3 dated 2025-04-14

Title: Estimates Degrees of Relatedness (Up to the Second Degree) for Extreme Low-Coverage Data
Description: The goal of the package is to provide an easy-to-use method for estimating degrees of relatedness (up to the second degree) for extreme low-coverage data. The package also allows users to quantify and visualise the level of confidence in the estimated degrees of relatedness.
Author: Jono Tuke [aut, cre] , Adam B. Rohrlach [aut] , Wolfgang Haak [aut] , Divyaratan Popli [aut]
Maintainer: Jono Tuke <simon.tuke@adelaide.edu.au>

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Package blatent updated to version 0.1.3 with previous version 0.1.2 dated 2023-12-08

Title: Bayesian Latent Variable Models
Description: Estimation of latent variable models using Bayesian methods. Currently estimates the loglinear cognitive diagnosis model of Henson, Templin, and Willse (2009) <doi:10.1007/s11336-008-9089-5>.
Author: Jonathan Templin [aut, cre]
Maintainer: Jonathan Templin <jtempli@clemson.edu>

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Package biogeom updated to version 1.5.1 with previous version 1.5.0 dated 2025-08-24

Title: Biological Geometries
Description: Is used to simulate and fit biological geometries. 'biogeom' incorporates several novel universal parametric equations that can generate the profiles of bird eggs, flowers, linear and lanceolate leaves, seeds, starfish, and tree-rings (Gielis (2003) <doi:10.3732/ajb.90.3.333>; Shi et al. (2020) <doi:10.3390/sym12040645>), three growth-rate curves representing the ontogenetic growth trajectories of animals and plants against time, and the axially symmetrical and integral forms of all these functions (Shi et al. (2017) <doi:10.1016/j.ecolmodel.2017.01.012>; Shi et al. (2021) <doi:10.3390/sym13081524>). The optimization method proposed by Nelder and Mead (1965) <doi:10.1093/comjnl/7.4.308> was used to estimate model parameters. 'biogeom' includes several real data sets of the boundary coordinates of natural shapes, including avian eggs, fruit, lanceolate and ovate leaves, tree rings, seeds, and sea stars,and can be potentially applied to other natural shapes. [...truncated...]
Author: Peijian Shi [aut, cre], Johan Gielis [aut], Brady K. Quinn [aut]
Maintainer: Peijian Shi <pjshi@njfu.edu.cn>

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Package LobsterCatch (with last version 0.1.0) was removed from CRAN

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

2023-06-19 0.1.0

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Package leidenAlg updated to version 1.1.7 with previous version 1.1.6-1 dated 2026-04-15

Title: Implements the Leiden Algorithm via an R Interface
Description: An R interface to the Leiden algorithm, an iterative community detection algorithm on networks. The algorithm is designed to converge to a partition in which all subsets of all communities are locally optimally assigned, yielding communities guaranteed to be connected. The implementation proves to be fast, scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The original implementation was constructed as a python interface "leidenalg" found here: <https://github.com/vtraag/leidenalg>. The algorithm was originally described in Traag, V.A., Waltman, L. & van Eck, N.J. "From Louvain to Leiden: guaranteeing well-connected communities". Sci Rep 9, 5233 (2019) <doi:10.1038/s41598-019-41695-z>.
Author: Peter Kharchenko [aut], Viktor Petukhov [aut], Yichen Wang [aut], V.A. Traag [ctb], Gabor Csardi [ctb], Tamas Nepusz [ctb], Minh Van Nguyen [ctb], Evan Biederstedt [cre, aut]
Maintainer: Evan Biederstedt <evan.biederstedt@gmail.com>

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 leidenAlg-1.1.7/leidenAlg/src/rigraph/Makefile           |    2 
 leidenAlg-1.1.7/leidenAlg/src/rigraph/Makefile.win       |    2 
 leidenAlg-1.1.7/leidenAlg/src/rigraph/rinterface.c       |   32 ++++++++
 leidenAlg-1.1.7/leidenAlg/src/rigraph/rinterface_extra.c |   57 +++++++++++++--
 8 files changed, 89 insertions(+), 12 deletions(-)

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Package engression updated to version 0.1.6 with previous version 0.1.5 dated 2026-01-07

Title: Engression Modelling
Description: Fits engression models for nonlinear distributional regression. Predictors and targets can be univariate or multivariate. Functionality includes estimation of conditional mean, estimation of conditional quantiles, or sampling from the fitted distribution. Training is done full-batch on CPU (the python version offers GPU-accelerated stochastic gradient descent). Based on "Engression: Extrapolation through the lens of distributional regression" by Xinwei Shen and Nicolai Meinshausen (2024) in JRSSB. Also supports classification (experimental). <doi:10.1093/jrsssb/qkae108>.
Author: Xinwei Shen [aut], Nicolai Meinshausen [aut, cre]
Maintainer: Nicolai Meinshausen <meinshausen@stat.math.ethz.ch>

Diff between engression versions 0.1.5 dated 2026-01-07 and 0.1.6 dated 2026-04-16

 DESCRIPTION               |    6 +++---
 MD5                       |   19 ++++++++++---------
 NEWS.md                   |only
 R/engression.R            |   20 +++++++++++---------
 R/engressionfit.R         |    4 ++--
 R/predict.engression.R    |   17 +++++++++--------
 R/print.engression.R      |    6 ++++--
 man/engression.Rd         |   10 ++++++----
 man/engressionfit.Rd      |    4 ++--
 man/predict.engression.Rd |    6 +++---
 man/print.engression.Rd   |    4 +++-
 11 files changed, 53 insertions(+), 43 deletions(-)

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Package countrycode updated to version 1.8.0 with previous version 1.7.0 dated 2026-02-27

Title: Convert Country Names and Country Codes
Description: Standardize country names, convert them into one of 40 different coding schemes, convert between coding schemes, and assign region descriptors.
Author: Vincent Arel-Bundock [aut, cre] , CJ Yetman [ctb] , Nils Enevoldsen [ctb] , Etienne Bacher [ctb] , Samuel Meichtry [ctb]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

Diff between countrycode versions 1.7.0 dated 2026-02-27 and 1.8.0 dated 2026-04-16

 DESCRIPTION                          |    6 +++---
 MD5                                  |   20 ++++++++++----------
 NEWS.md                              |    5 +++++
 R/codelist.R                         |    1 +
 R/countrycode.R                      |    8 +++++---
 data/codelist.rda                    |binary
 data/codelist_panel.rda              |binary
 man/codelist.Rd                      |    1 +
 tests/testthat/test-corner-cases.R   |    3 +++
 tests/testthat/test-regex-internal.R |   34 ++++++++++++++++++++++------------
 tests/testthat/test-regex-special.R  |    5 +++++
 11 files changed, 55 insertions(+), 28 deletions(-)

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