Mon, 17 Nov 2025

Package umx updated to version 4.60.0 with previous version 4.59.0 dated 2025-10-21

Title: Structural Equation Modeling and Twin Modeling in R
Description: Quickly create, run, and report structural equation models, and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. <doi:10.1017/thg.2019.2>.
Author: Timothy C. Bates [aut, cre] , Nathan Gillespie [wit], Hermine Maes [ctb], Michael C. Neale [ctb], Joshua N. Pritikin [ctb], Luis De Araujo [ctb], Brenton Wiernik [ctb], Michael Zakharin [wit]
Maintainer: Timothy C. Bates <timothy.c.bates@gmail.com>

Diff between umx versions 4.59.0 dated 2025-10-21 and 4.60.0 dated 2025-11-17

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Package turkeyelections updated to version 0.1.4 with previous version 0.1.3 dated 2025-11-13

Title: The Most Comprehensive R Package for Turkish Election Results
Description: Includes the results of general, local, and presidential elections held in Turkey between 1995 and 2024, broken down by provinces and overall national results. It facilitates easy processing of this data and the creation of visual representations based on these election results.
Author: Ozancan Ozdemir [aut, cre]
Maintainer: Ozancan Ozdemir <ozancanozdemir@gmail.com>

Diff between turkeyelections versions 0.1.3 dated 2025-11-13 and 0.1.4 dated 2025-11-17

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Package tikatuwq updated to version 0.8.0 with previous version 0.7.3 dated 2025-10-31

Title: Water Quality Assessment and Environmental Compliance in Brazil
Description: Tools to import, clean, validate, and analyze freshwater quality data in Brazil. Implements water quality indices including the Water Quality Index (WQI/IQA), the Trophic State Index (TSI/IET) after Carlson (1977) <doi:10.4319/lo.1977.22.2.0361> and Lamparelli (2004) <https://www.teses.usp.br/teses/disponiveis/41/41134/tde-20032006-075813/publico/TeseLamparelli2004.pdf>, and the National Sanitation Foundation Water Quality Index (NSF WQI) <doi:10.1007/s11157-023-09650-7>. The package also checks compliance with Brazilian standard CONAMA Resolution 357/2005 <https://conama.mma.gov.br/?id=450&option=com_sisconama&task=arquivo.download> and generates reproducible reports for routine monitoring workflows. The example dataset (`wq_demo`) is now a real subset from monitoring data (BURANHEM river, 2020-2024, 4 points, 20 rows, 14 columns including extra `rio`, `lat`, `lon`). All core examples and vignettes use this realistic sample, improving reproducibility an [...truncated...]
Author: Vinicius Saraiva Santos [aut, cre]
Maintainer: Vinicius Saraiva Santos <vinisaraiva@gmail.com>

Diff between tikatuwq versions 0.7.3 dated 2025-10-31 and 0.8.0 dated 2025-11-17

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Package SimInf updated to version 10.1.0 with previous version 10.0.0 dated 2025-11-13

Title: A Framework for Data-Driven Stochastic Disease Spread Simulations
Description: Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>. The package also provides function [...truncated...]
Author: Stefan Widgren [aut, cre] , Robin Eriksson [aut] , Stefan Engblom [aut] , Pavol Bauer [aut] , Thomas Rosendal [ctb] , Ivana Rodriguez Ewerloef [ctb] , Attractive Chaos [cph]
Maintainer: Stefan Widgren <stefan.widgren@gmail.com>

Diff between SimInf versions 10.0.0 dated 2025-11-13 and 10.1.0 dated 2025-11-17

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Package sgapi readmission to version 1.1.1 with previous version 1.1.0 dated 2025-05-08

Title: Aid Querying 'nomis' and 'Office for National Statistics Open Geography' APIs
Description: Facilitates extraction of geospatial data from the 'Office for National Statistics Open Geography' and 'nomis' Application Programming Interfaces (APIs). Simplifies process of querying 'nomis' datasets <https://www.nomisweb.co.uk/> and extracting desired datasets in dataframe format. Extracts area shapefiles at chosen resolution from 'Office for National Statistics Open Geography' <https://geoportal.statistics.gov.uk/>.
Author: Michael Stocks [aut, cre], Andrew Christy [aut], James Macpherson [aut], Hadyn Jenkins [aut], Crown Copyright [cph]
Maintainer: Michael Stocks <sgapi.orhub@gmail.com>

This is a re-admission after prior archival of version 1.1.0 dated 2025-05-08

Diff between sgapi versions 1.1.0 dated 2025-05-08 and 1.1.1 dated 2025-11-17

 DESCRIPTION                           |    6 +++---
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New package SCoRES with initial version 0.1.2
Package: SCoRES
Title: Simultaneous Confidence Region Excursion Sets
Version: 0.1.2
Author: Zhuoran Yu [aut, cre], Armin Schwartzman [aut], Junting Ren [aut], Julia Wrobel [aut]
Maintainer: Zhuoran Yu <angela.yu@emory.edu>
Description: Provides computational tools for estimating inverse regions and constructing the corresponding simultaneous outer and inner confidence regions. Acceptable input includes both one-dimensional and two-dimensional data for linear, logistic, functional, and spatial generalized least squares regression models. Functions are also available for constructing simultaneous confidence bands (SCBs) for these models. The definition of simultaneous confidence regions (SCRs) follows Sommerfeld et al. (2018) <doi:10.1080/01621459.2017.1341838>. Methods for estimating inverse regions, SCRs, and the nonparametric bootstrap are based on Ren et al. (2024) <doi:10.1093/jrsssc/qlae027>. Methods for constructing SCBs are described in Crainiceanu et al. (2024) <doi:10.1201/9781003278726> and Telschow et al. (2022) <doi:10.1016/j.jspi.2021.05.008>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://angelayustat.github.io/SCoRES/
BugReports: https://github.com/AngelaYuStat/SCoRES/issues
Imports: dplyr, forcats, ggplot2, grDevices, patchwork, MASS, Matrix, matrixStats, metR, nlme, stats, tidyr, refund, reshape, tibble, rlang, magrittr, utils
Depends: R (>= 4.4)
LazyData: true
Suggests: knitr, mgcv, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, rmarkdown
BuildVignettes: true
LazyLoad: no
ByteCompile: false
NeedsCompilation: no
Packaged: 2025-11-12 23:27:25 UTC; PC
Repository: CRAN
Date/Publication: 2025-11-17 21:20:12 UTC

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New package rclsp with initial version 0.1.0
Package: rclsp
Title: A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems
Version: 0.1.0
Description: Convex Least Squares Programming (CLSP) is a two-step estimator for solving underdetermined, ill-posed, or structurally constrained least-squares problems. It combines pseudoinverse-based estimation with convex-programming correction methods inspired by Lasso, Ridge, and Elastic Net to ensure numerical stability, constraint enforcement, and interpretability. The package also provides numerical stability analysis and CLSP-specific diagnostics, including partial R^2, normalized RMSE (NRMSE), Monte Carlo t-tests for mean NRMSE, and condition-number-based confidence bands.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.2)
Imports: Matrix, stats, methods, CVXR, MASS
Suggests: testthat (>= 3.0.0)
URL: https://github.com/econcz/rclsp
BugReports: https://github.com/econcz/rclsp/issues
NeedsCompilation: no
Packaged: 2025-11-13 00:02:15 UTC; ilyabolotov
Author: Ilya Bolotov [aut, cre]
Maintainer: Ilya Bolotov <ilya.bolotov@vse.cz>
Repository: CRAN
Date/Publication: 2025-11-17 21:10:02 UTC

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New package privacyR with initial version 1.0.0
Package: privacyR
Title: Privacy-Preserving Data Anonymization
Version: 1.0.0
Description: Tools for anonymizing sensitive patient and research data. Helps protect privacy while keeping data useful for analysis. Anonymizes IDs, names, dates, locations, and ages while maintaining referential integrity. Methods based on: Sweeney (2002) <doi:10.1142/S0218488502001648>, Dwork et al. (2006) <doi:10.1007/11681878_14>, El Emam et al. (2011) <doi:10.1371/journal.pone.0028071>, Fung et al. (2010) <doi:10.1145/1749603.1749605>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: lubridate
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, data.table
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-13 02:05:13 UTC; vikrant31
Author: Vikrant Dev Rathore [aut, cre]
Maintainer: Vikrant Dev Rathore <rathore.vikrant@gmail.com>
Repository: CRAN
Date/Publication: 2025-11-17 21:20:02 UTC

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Package pda updated to version 1.3.0 with previous version 1.2.8 dated 2025-03-10

Title: Privacy-Preserving Distributed Algorithms
Description: A collection of privacy-preserving distributed algorithms (PDAs) for conducting federated statistical learning across multiple data sites. The PDA framework includes models for various tasks such as regression, trial emulation, causal inference, design-specific analysis, and clustering. The PDA algorithms run on a lead site and only require summary statistics from collaborating sites, with one or few iterations. The package can be used together with the online data transfer system (<https://pda-ota.pdamethods.org/>) for safe and convenient collaboration. For more information, please visit our software websites: <https://github.com/Penncil/pda>, and <https://pdamethods.org/>.
Author: Chongliang Luo [cre], Rui Duan [aut], Mackenzie Edmondson [aut], Jiayi Tong [aut], Xiaokang Liu [aut], Kenneth Locke [aut], Jie Hu [aut], Bingyu Zhang [aut], Yicheng Shen [aut], Yudong Wang [aut], Yiwen Lu [aut], Lu Li [aut], Yong Chen [aut], Penn Co [...truncated...]
Maintainer: Chongliang Luo <luocl3009@gmail.com>

Diff between pda versions 1.2.8 dated 2025-03-10 and 1.3.0 dated 2025-11-17

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Package PAGFL updated to version 1.1.4 with previous version 1.1.3 dated 2025-02-20

Title: Joint Estimation of Latent Groups and Group-Specific Coefficients in (Time-Varying) Panel Data Models
Description: Latent group structures are a common challenge in panel data analysis. Disregarding group-level heterogeneity can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty. This package addresses the issue of unobservable group structures by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) <doi:10.1016/j.jeconom.2022.12.002>. PAGFL identifies latent group structures and group-specific coefficients in a single step. On top of that, we extend the PAGFL to time-varying coefficient functions (FUSE-TIME), following Haimerl et al. (2025) <doi:10.48550/arXiv.2503.23165>.
Author: Paul Haimerl [aut, cre] , Stephan Smeekes [ctb] , Ines Wilms [ctb] , Ali Mehrabani [ctb]
Maintainer: Paul Haimerl <paul.haimerl@econ.au.dk>

Diff between PAGFL versions 1.1.3 dated 2025-02-20 and 1.1.4 dated 2025-11-17

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New package nycOpenData with initial version 0.1.2
Package: nycOpenData
Title: Convenient Access to NYC Open Data API Endpoints
Version: 0.1.2
Description: Provides a unified set of helper functions to access datasets from the NYC Open Data platform <https://opendata.cityofnewyork.us/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package includes endpoints for 311 service requests, DOB job applications, juvenile justice metrics, school safety, environmental data, event permitting, and additional citywide datasets.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: httr, jsonlite, tibble
Suggests: knitr, rmarkdown
URL: https://github.com/martinezc1/nycOpenData
BugReports: https://github.com/martinezc1/nycOpenData/issues
NeedsCompilation: no
Packaged: 2025-11-13 04:15:08 UTC; christianmartinez
Author: Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2025-11-17 21:30:02 UTC

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Package matsindf updated to version 0.4.11 with previous version 0.4.10 dated 2025-05-26

Title: Matrices in Data Frames
Description: Provides functions to collapse a tidy data frame into matrices in a data frame and expand a data frame of matrices into a tidy data frame.
Author: Matthew Heun [aut, cre]
Maintainer: Matthew Heun <matthew.heun@me.com>

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Package LorMe updated to version 2.0.1 with previous version 2.0.0 dated 2025-11-16

Title: Lightweight One-Line Resolving Microbial Ecology Program
Description: Provides a robust collection of functions tailored for microbial ecology analysis, encompassing both data analysis and visualization. It introduces an encapsulation feature that streamlines the process into a summary object. With the initial configuration of this summary object, users can execute a wide range of analyses with a single line of code, requiring only two essential parameters for setup. The package delivers comprehensive outputs including analysis objects, statistical outcomes, and visualization-ready data, enhancing the efficiency of research workflows. Designed with user-friendliness in mind, it caters to both novices and seasoned researchers, offering an intuitive interface coupled with adaptable customization options to meet diverse analytical needs.
Author: Ningqi Wang [aut, cre, cph], Yaozhong Zhang [aut], Gaofei Jiang [aut]
Maintainer: Ningqi Wang <2434066068@qq.com>

Diff between LorMe versions 2.0.0 dated 2025-11-16 and 2.0.1 dated 2025-11-17

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Package HIMA updated to version 2.3.3 with previous version 2.3.2 dated 2025-06-11

Title: High-Dimensional Mediation Analysis
Description: Allows to estimate and test high-dimensional mediation effects based on advanced mediator screening and penalized regression techniques. Methods used in the package refer to Zhang H, Zheng Y, Hou L, Liu L, HIMA: An R Package for High-Dimensional Mediation Analysis. Journal of Data Science. (2025). <doi:10.6339/25-JDS1192>.
Author: Yinan Zheng [aut, cre] , Haixiang Zhang [aut], Lifang Hou [aut], Lei Liu [aut, cph]
Maintainer: Yinan Zheng <y-zheng@northwestern.edu>

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Package hdf5lib readmission to version 1.14.6.7 with previous version 1.14.6.4 dated 2025-11-10

Title: Headers and Static Libraries for 'HDF5'
Description: 'HDF5' (Hierarchical Data Format 5) is a high-performance library and file format for storing and managing large, complex data. This package provides the static libraries and headers for the 'HDF5' 'C' library (release 1.14.6). It is intended for R package developers to use in the 'LinkingTo' field, which eliminates the need for users to install system-level 'HDF5' dependencies. This build is compiled with thread-safety enabled and supports dynamic loading of external compression filters. 'HDF5' is developed by 'The HDF Group' <https://www.hdfgroup.org/>.
Author: Daniel P. Smith [aut, cre] , The HDF Group [cph] , Jean-loup Mark [cph] , Gailly Adler [cph]
Maintainer: Daniel P. Smith <dansmith01@gmail.com>

This is a re-admission after prior archival of version 1.14.6.4 dated 2025-11-10

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New package fmi with initial version 0.1.7
Package: fmi
Title: Hierarchical Permutation Tests for Functional Measurement Invariance
Description: Provides a suite of functions to test for Functional Measurement Invariance (FMI) between two groups. Implements hierarchical permutation tests for configural, metric, and scalar invariance, adapting concepts from Multi-Group Confirmatory Factor Analysis (MGCFA) to functional data. Methods are based on concepts from: Meredith, W. (1993) <doi:10.1007/BF02294825>,5 Yao, F., Müller, H. G., & Wang, J. L. (2005) <doi:10.1198/016214504000001745>, and Lee, K. Y., & Li, L. (2022) <doi:10.1111/rssb.12471>.
Version: 0.1.7
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, ggplot2, knitr, magrittr, methods, purrr, refund, stats, tibble, tidyr, utils
Suggests: fda, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-13 02:14:30 UTC; user
Author: Hyeri Kim [aut, cre]
Maintainer: Hyeri Kim <gpfl3616@naver.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2025-11-17 21:20:07 UTC

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Package fec16 updated to version 0.1.6 with previous version 0.1.5 dated 2025-09-01

Title: Data Package for the 2016 United States Federal Elections
Description: Easily analyze relational data from the United States 2016 federal election cycle as reported by the Federal Election Commission. This package contains data about candidates, committees, and a variety of different financial expenditures. Data is from <https://www.fec.gov/data/browse-data/?tab=bulk-data>.
Author: Marium Tapal [aut, cre] , Rana Gahwagy [aut], Irene Ryan [aut], Benjamin S. Baumer [aut]
Maintainer: Marium Tapal <mariumtapal@gmail.com>

Diff between fec16 versions 0.1.5 dated 2025-09-01 and 0.1.6 dated 2025-11-17

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Package farr updated to version 1.0.0 with previous version 0.3.2 dated 2025-09-01

Title: Data and Code for Empirical Research in Accounting
Description: Handy functions and data to support the course book 'Empirical Research in Accounting: Tools and Methods' (1st ed.). Chapman and Hall/CRC. <doi:10.1201/9781003456230> and <https://iangow.github.io/far_book/>.
Author: Ian Gow [aut, cre]
Maintainer: Ian Gow <iandgow@gmail.com>

Diff between farr versions 0.3.2 dated 2025-09-01 and 1.0.0 dated 2025-11-17

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Package duckdb updated to version 1.4.2 with previous version 1.4.1 dated 2025-10-16

Title: DBI Package for the DuckDB Database Management System
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and an R Database Interface (DBI) connector.
Author: Hannes Muehleisen [aut] , Mark Raasveldt [aut] , Kirill Mueller [cre] , Stichting DuckDB Foundation [cph], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrocher [...truncated...]
Maintainer: Kirill Mueller <kirill@cynkra.com>

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Package CohortGenerator updated to version 1.0.1 with previous version 1.0.0 dated 2025-11-12

Title: Cohort Generation for the OMOP Common Data Model
Description: Generate cohorts and subsets using an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. Cohorts are defined using 'CIRCE' (<https://github.com/ohdsi/circe-be>) or SQL compatible with 'SqlRender' (<https://github.com/OHDSI/SqlRender>).
Author: Anthony Sena [aut, cre], Jamie Gilbert [aut], Gowtham Rao [aut], Freddy Avila Cruz [aut], Martijn Schuemie [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Anthony Sena <sena@ohdsi.org>

Diff between CohortGenerator versions 1.0.0 dated 2025-11-12 and 1.0.1 dated 2025-11-17

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New package casimir with initial version 0.3.3
Package: casimir
Title: Comparing Automated Subject Indexing Methods in R
Version: 0.3.3
Description: Perform evaluation of automatic subject indexing methods. The main focus of the package is to enable efficient computation of set retrieval and ranked retrieval metrics across multiple dimensions of a dataset, e.g. document strata or subsets of the label set. The package also provides the possibility of computing bootstrap confidence intervals for all major metrics, with seamless integration of parallel computation and propensity scored variants of standard metrics.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr (>= 1.1.1), furrr, purrr, rsample, tidyr, rlang, collapse (>= 2.1.0), stringr, options, withr
Suggests: testthat (>= 3.0.0), tibble, tidyverse, ggplot2, future
Depends: R (>= 4.1.0)
LazyData: true
URL: https://deutsche-nationalbibliothek.github.io/casimir/
NeedsCompilation: no
Packaged: 2025-11-13 07:50:18 UTC; maximilian
Author: Maximilian Kaehler [aut, cre] , Markus Schumacher [aut], Deutsche Nationalbibliothek [cph]
Maintainer: Maximilian Kaehler <m.kaehler@dnb.de>
Repository: CRAN
Date/Publication: 2025-11-17 21:30:07 UTC

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New package bin2norm with initial version 0.1.0
Package: bin2norm
Title: Hierarchical Probit Estimation for Dichotomized Data
Version: 0.1.0
Description: Provides likelihood-based and hierarchical estimation methods for thresholded (binomial-probit) data. Supports fixed-mean and random-mean models with maximum likelihood estimation (MLE), generalized linear mixed model (GLMM), and Bayesian Markov chain Monte Carlo (MCMC) implementations. For methodological background, see Albert and Chib (1993) <doi:10.1080/01621459.1993.10476321> and McCulloch (1994) <doi:10.2307/2297959>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: lme4, rstan, stats, statmod
NeedsCompilation: no
Packaged: 2025-11-12 18:52:57 UTC; zhaoze
Author: Zhaoze Liu [aut, cre]
Maintainer: Zhaoze Liu <786633848@qq.com>
Repository: CRAN
Date/Publication: 2025-11-17 21:10:13 UTC

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Package autodb updated to version 3.2.4 with previous version 3.1.0 dated 2025-09-18

Title: Automatic Database Normalisation for Data Frames
Description: Automatic normalisation of a data frame to third normal form, with the intention of easing the process of data cleaning. (Usage to design your actual database for you is not advised.) Originally inspired by the 'AutoNormalize' library for 'Python' by 'Alteryx' (<https://github.com/alteryx/autonormalize>), with various changes and improvements. Automatic discovery of functional or approximate dependencies, normalisation based on those, and plotting of the resulting "database" via 'Graphviz', with options to exclude some attributes at discovery time, or remove discovered dependencies at normalisation time.
Author: Mark Webster [aut, cre]
Maintainer: Mark Webster <markwebster204@yahoo.co.uk>

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Package aedseo updated to version 1.0.0 with previous version 0.3.0 dated 2025-04-09

Title: Automated and Early Detection of Seasonal Epidemic Onset and Burden Levels
Description: A powerful tool for automating the early detection of seasonal epidemic onsets in time series data. It offers the ability to estimate growth rates across consecutive time intervals, calculate the sum of cases (SoC) within those intervals, and estimate seasonal onsets within user defined seasons. With use of a disease-specific threshold it also offers the possibility to estimate seasonal onset of epidemics. Additionally it offers the ability to estimate burden levels for seasons based on historical data. It is aimed towards epidemiologists, public health professionals, and researchers seeking to identify and respond to seasonal epidemics in a timely fashion.
Author: Sofia Myrup Otero [aut] , Kasper Schou Telkamp [aut] , Lasse Engbo Christiansen [aut, cre] , Rasmus Skytte Randloev [rev] , Statens Serum Institut, SSI [cph, fnd]
Maintainer: Lasse Engbo Christiansen <lsec@ssi.dk>

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 aedseo-1.0.0/aedseo/tests/testthat/test-generate_seasonal_data.R     |   46 +-
 aedseo-1.0.0/aedseo/tests/testthat/test-historical_summary.R         |   54 ++
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New package riemstats with initial version 0.2.0
Package: riemstats
Title: Riemannian ANOVA Statistics
Version: 0.2.0
Description: Provides statistical methods for analyzing samples of symmetric positive definite (SPD) matrices, particularly functional connectivity matrices from neuroimaging data. Implements Fréchet ANOVA (Dubey and Müller (2019) <doi:10.1093/biomet/asz052>) for testing differences between groups in metric spaces, and Riemannian ANOVA methods that leverage tangent space geometry with classic multivariate test statistics including Wilks' Lambda and Pillai's trace. Also includes harmonization techniques for removing batch effects in multi-site studies: ComBat-based harmonization (Honnorat et al. (2024) <doi:10.1016/j.media.2023.103043>) and rigid harmonization (Simeon et al. (2022) <doi:10.3389/fninf.2022.769274>). Builds on 'riemtan' package infrastructure for efficient computation with multiple Riemannian metrics.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: Matrix, CovTools, sva, purrr, riemtan, methods
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://nicoesve.github.io/riemstats/
BugReports: https://github.com/nicoesve/riemstats/issues
Maintainer: Nicolas Escobar <nescoba@iu.edu>
NeedsCompilation: no
Packaged: 2025-11-12 14:27:13 UTC; new user
Author: Nicolas Escobar [aut, cre] , Jaroslaw Harezlak [ths]
Repository: CRAN
Date/Publication: 2025-11-17 21:00:02 UTC

More information about riemstats at CRAN
Permanent link

New package PCBN with initial version 0.1.1
Package: PCBN
Title: Inference of Pair-Copula Bayesian Networks
Version: 0.1.1
Description: Creates, fits and samples Pair-Copula Bayesian networks (PCBN) under some restrictions on the underlying Directed Acyclic Graph (DAG), that is, no active cycles nor interfering v-structures, following Derumigny, Horsman and Kurowicka (2025) <doi:10.48550/arXiv.2510.03518>.
License: GPL (>= 2)
Encoding: UTF-8
Imports: bnlearn, igraph, r2r, VineCopula
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), data.tree, Rgraphviz
URL: https://github.com/AlexisDerumigny/PCBN
BugReports: https://github.com/AlexisDerumigny/PCBN/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-12 16:20:32 UTC; aderumigny
Author: Alexis Derumigny [aut, cre] , Niels Horsman [aut], Dorota Kurowicka [aut]
Maintainer: Alexis Derumigny <a.f.f.derumigny@tudelft.nl>
Repository: CRAN
Date/Publication: 2025-11-17 21:00:07 UTC

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New package GeneralizedUmatrixGPU with initial version 0.1.8
Package: GeneralizedUmatrixGPU
Title: Credible Visualization for Two-Dimensional Projections of Data
Version: 0.1.8
Date: 2025-11-04
Maintainer: Quirin Stier <Quirin_Stier@gmx.de>
Description: Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018] <DOI: 10.1007/978-3-658-20540-9>. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9> and the main algorithm called simplified self-organizing map for dimensionality reduction methods is published in Thrun, M.C. and Ultsch, A.: "Uncovering High-dimensional Structures of Projections from Dimension [...truncated...]
License: GPL-3
Imports: Rcpp (>= 1.0.8), RcppParallel (>= 5.1.4), ggplot2, GeneralizedUmatrix
Suggests: DataVisualizations, rgl, grid, mgcv, png, reshape2, fields, ABCanalysis, plotly, deldir, methods, knitr (>= 1.12), rmarkdown (>= 0.9), ProjectionBasedClustering
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Depends: R (>= 3.0)
NeedsCompilation: yes
SystemRequirements: GNU make, pandoc (>=1.12.3, needed for vignettes), OpenCL shared library (provided by an SDK such as AMD/NVIDIA)
LazyLoad: yes
LazyData: TRUE
Encoding: UTF-8
Packaged: 2025-11-12 11:01:36 UTC; quiri
Author: Quirin Stier [aut, cre] , Michael Thrun [aut, cph] , The Khronos Group Inc. [cph]
Repository: CRAN
Date/Publication: 2025-11-17 20:50:02 UTC

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Package epidatr updated to version 1.2.2 with previous version 1.2.1 dated 2025-03-20

Title: Client for Delphi's 'Epidata' API
Description: The Delphi 'Epidata' API provides real-time access to epidemiological surveillance data for influenza, 'COVID-19', and other diseases for the USA at various geographical resolutions, both from official government sources such as the Center for Disease Control (CDC) and Google Trends and private partners such as Facebook and Change 'Healthcare'. It is built and maintained by the Carnegie Mellon University Delphi research group. To cite this API: David C. Farrow, Logan C. Brooks, Aaron 'Rumack', Ryan J. 'Tibshirani', 'Roni' 'Rosenfeld' (2015). Delphi 'Epidata' API. <https://github.com/cmu-delphi/delphi-epidata>.
Author: Logan Brooks [aut], Dmitry Shemetov [aut], Samuel Gratzl [aut], David Weber [ctb, cre], Nat DeFries [ctb], Alex Reinhart [ctb], Daniel J. McDonald [ctb], Kean Ming Tan [ctb], Will Townes [ctb], George Haff [ctb], Kathryn Mazaitis [ctb]
Maintainer: David Weber <davidweb@andrew.cmu.edu>

Diff between epidatr versions 1.2.1 dated 2025-03-20 and 1.2.2 dated 2025-11-17

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Package sleev updated to version 1.1.6 with previous version 1.1.5 dated 2025-09-11

Title: Semiparametric Likelihood Estimation with Errors in Variables
Description: Efficient regression analysis under general two-phase sampling, where Phase I includes error-prone data and Phase II contains validated data on a subset.
Author: Sarah Lotspeich [aut], Ran Tao [aut, cre], Joey Sherrill [prg], Jiangmei Xiong [ctb]
Maintainer: Ran Tao <r.tao@vanderbilt.edu>

Diff between sleev versions 1.1.5 dated 2025-09-11 and 1.1.6 dated 2025-11-17

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Package tidyrgee updated to version 0.1.1 with previous version 0.1.0 dated 2022-09-15

Title: 'tidyverse' Methods for 'Earth Engine'
Description: Provides 'tidyverse' methods for wrangling and analyzing 'Earth Engine' <https://earthengine.google.com/> data. These methods help the user with filtering, joining and summarising 'Earth Engine' image collections.
Author: Zack Arno [aut, cre, cph], Josh Erickson [aut, cph]
Maintainer: Zack Arno <zackarno@gmail.com>

Diff between tidyrgee versions 0.1.0 dated 2022-09-15 and 0.1.1 dated 2025-11-17

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Package TH.data updated to version 1.1-5 with previous version 1.1-4 dated 2025-09-02

Title: TH's Data Archive
Description: Contains data sets used in other packages Torsten Hothorn maintains.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between TH.data versions 1.1-4 dated 2025-09-02 and 1.1-5 dated 2025-11-17

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Package rmpw updated to version 0.0.6 with previous version 0.0.5 dated 2024-03-05

Title: Causal Mediation Analysis Using Weighting Approach
Description: We implement causal mediation analysis using the methods proposed by Hong (2010) and Hong, Deutsch & Hill (2015) <doi:10.3102/1076998615583902>. It allows the estimation and hypothesis testing of causal mediation effects through ratio of mediator probability weights (RMPW). This strategy conveniently relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. We also implement a sensitivity analysis by extending the RMPW method to assess potential bias in the presence of omitted pretreatment or posttreatment covariates. The sensitivity analysis strategy was proposed by Hong, Qin, and Yang (2018) <doi:10.3102/1076998617749561>.
Author: Xu Qin [aut, cre], Guanglei Hong [aut], Fan Yang [aut]
Maintainer: Xu Qin <xuqin@uchicago.edu>

Diff between rmpw versions 0.0.5 dated 2024-03-05 and 0.0.6 dated 2025-11-17

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Package ChannelAttribution updated to version 2.2.3 with previous version 2.2.2 dated 2025-11-02

Title: Markov Model for Online Multi-Channel Attribution
Description: Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.
Author: Davide Altomare [cre, aut], David Loris [aut]
Maintainer: Davide Altomare <info@channelattribution.io>

Diff between ChannelAttribution versions 2.2.2 dated 2025-11-02 and 2.2.3 dated 2025-11-17

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Package multilevelPSA updated to version 1.3.1 with previous version 1.3.0 dated 2025-04-04

Title: Multilevel Propensity Score Analysis
Description: Conducts and visualizes propensity score analysis for multilevel, or clustered data. Bryer & Pruzek (2011) <doi:10.1080/00273171.2011.636693>.
Author: Jason Bryer [aut, cre]
Maintainer: Jason Bryer <jason@bryer.org>

Diff between multilevelPSA versions 1.3.0 dated 2025-04-04 and 1.3.1 dated 2025-11-17

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Package shapr updated to version 1.0.6 with previous version 1.0.5 dated 2025-08-25

Title: Prediction Explanation with Dependence-Aware Shapley Values
Description: Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements methods which accounts for any feature dependence, and thereby produces more accurate estimates of the true Shapley values. An accompanying 'Python' wrapper ('shaprpy') is available through the GitHub repository.
Author: Martin Jullum [cre, aut] , Lars Henry Berge Olsen [aut] , Annabelle Redelmeier [aut], Jon Lachmann [aut] , Nikolai Sellereite [aut] , Anders Loeland [ctb], Jens Christian Wahl [ctb], Camilla Lingjaerde [ctb], Norsk Regnesentral [cph, fnd]
Maintainer: Martin Jullum <Martin.Jullum@nr.no>

Diff between shapr versions 1.0.5 dated 2025-08-25 and 1.0.6 dated 2025-11-17

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 R/check_convergence.R                                                   |    2 
 R/cli.R                                                                 |    8 
 R/compute_estimates.R                                                   |    4 
 R/compute_vS.R                                                          |    4 
 R/explain.R                                                             |    4 
 R/explain_forecast.R                                                    |    2 
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 R/get_results.R                                                         |   10 
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 R/shapley_setup.R                                                       |    4 
 R/summary.R                                                             |   13 
 R/timing.R                                                              |    2 
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 man/cli_compute_vS.Rd                                                   |    4 
 man/cli_iter.Rd                                                         |    4 
 man/cli_startup.Rd                                                      |    4 
 man/compute_estimates.Rd                                                |    4 
 man/compute_shapley.Rd                                                  |    4 
 man/compute_time.Rd                                                     |    4 
 man/compute_vS.Rd                                                       |    4 
 man/explain.Rd                                                          |    2 
 man/explain_forecast.Rd                                                 |    2 
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 man/get_results.Rd                                                      |   11 
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 man/plot.shapr.Rd                                                       |   21 
 man/plot_MSEv_eval_crit.Rd                                              |    4 
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 man/prepare_data_causal.Rd                                              |    2 
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 man/print.shapr.Rd                                                      |    4 
 man/print_iter.Rd                                                       |    4 
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 man/round_manual.Rd                                                     |   44 
 man/save_results.Rd                                                     |    4 
 man/setup.Rd                                                            |    4 
 man/shapley_setup.Rd                                                    |    4 
 man/summary.shapr.Rd                                                    |    4 
 man/testing_cleanup.Rd                                                  |    4 
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 man/vaeac_train_model.Rd                                                |    2 
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 man/weight_matrix.Rd                                                    |    4 
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Package refund updated to version 0.1-38 with previous version 0.1-37 dated 2024-09-20

Title: Regression with Functional Data
Description: Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.
Author: Jeff Goldsmith [aut], Fabian Scheipl [aut], Lei Huang [aut], Julia Wrobel [aut, cre], Chongzhi Di [aut], Jonathan Gellar [aut], Jaroslaw Harezlak [aut], Mathew W. McLean [aut], Bruce Swihart [aut], Luo Xiao [aut], Ciprian Crainiceanu [aut], Philip T. [...truncated...]
Maintainer: Julia Wrobel <julia.wrobel@emory.edu>

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Package evola updated to version 1.0.7 with previous version 1.0.6 dated 2025-07-30

Title: Evolutionary Algorithm
Description: Runs an evolutionary algorithm using the 'AlphaSimR' machinery <doi:10.1093/g3journal/jkaa017> .
Author: Giovanny Covarrubias-Pazaran [aut, cre]
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Package SSDforR updated to version 2.3 with previous version 2.2 dated 2025-10-18

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
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Package thisutils updated to version 0.3.1 with previous version 0.2.0 dated 2025-10-05

Title: Collection of Utility Functions for Data Analysis and Computing
Description: Provides utility functions for data analysis and scientific computing. Includes functions for parallel processing, and other computational tasks to streamline workflows.
Author: Meng Xu [aut, cre]
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Package teal updated to version 1.1.0 with previous version 1.0.0 dated 2025-08-20

Title: Exploratory Web Apps for Analyzing Clinical Trials Data
Description: A 'shiny' based interactive exploration framework for analyzing clinical trials data. 'teal' currently provides a dynamic filtering facility and different data viewers. 'teal' 'shiny' applications are built using standard 'shiny' modules.
Author: Dawid Kaledkowski [aut, cre] , Pawel Rucki [aut], Aleksander Chlebowski [aut] , Andre Verissimo [aut] , Kartikeya Kirar [aut], Vedha Viyash [aut], Marcin Kosinski [aut], Adrian Waddell [aut], Dony Unardi [rev], Nina Qi [rev], Nikolas Burkoff [aut], M [...truncated...]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@roche.com>

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Package PublicationBiasBenchmark updated to version 0.1.1 with previous version 0.1.0 dated 2025-11-05

Title: Benchmark for Publication Bias Correction Methods
Description: Implements a unified interface for benchmarking meta-analytic publication bias correction methods through simulation studies (see Bartoš et al., 2025, <doi:10.48550/arXiv.2510.19489>). It provides 1) predefined data-generating mechanisms from the literature, 2) functions for running meta-analytic methods on simulated data, 3) pre-simulated datasets and pre-computed results for reproducible benchmarks, 4) tools for visualizing and comparing method performance.
Author: Frantisek Bartos [aut, cre] , Samuel Pawel [aut] , Bjoern S. Siepe [aut]
Maintainer: Frantisek Bartos <f.bartos96@gmail.com>

Diff between PublicationBiasBenchmark versions 0.1.0 dated 2025-11-05 and 0.1.1 dated 2025-11-17

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Package greeks updated to version 1.5.1 with previous version 1.4.4 dated 2025-03-02

Title: Sensitivities of Prices of Financial Options and Implied Volatilities
Description: Methods to calculate sensitivities of financial option prices for European, geometric and arithmetic Asian, and American options, with various payoff functions in the Black Scholes model, and in more general jump diffusion models. A shiny app to interactively plot the results is included. Furthermore, methods to compute implied volatilities are provided for a wide range of option types and custom payoff functions. Classical formulas are implemented for European options in the Black Scholes Model, as is presented in Hull, J. C. (2017), Options, Futures, and Other Derivatives. In the case of Asian options, Malliavin Monte Carlo Greeks are implemented, see Hudde, A. & Rüschendorf, L. (2023). European and Asian Greeks for exponential Lévy processes. <doi:10.1007/s11009-023-10014-5>. For American options, the Binomial Tree Method is implemented, as is presented in Hull, J. C. (2017).
Author: Anselm Hudde [aut, cre]
Maintainer: Anselm Hudde <anselmhudde@gmx.de>

Diff between greeks versions 1.4.4 dated 2025-03-02 and 1.5.1 dated 2025-11-17

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Package espadon updated to version 1.11.3 with previous version 1.11.1 dated 2025-06-26

Title: Easy Study of Patient DICOM Data in Oncology
Description: Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.
Author: Cathy Fontbonne [aut, cre] , Jean-Marc Fontbonne [aut] , Nathan Azemar [ctb]
Maintainer: Cathy Fontbonne <contact.espadon@lpccaen.in2p3.fr>

Diff between espadon versions 1.11.1 dated 2025-06-26 and 1.11.3 dated 2025-11-17

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Package EvalTest updated to version 1.0.5 with previous version 1.0.3 dated 2025-10-15

Title: A 'shiny' App to Evaluate Diagnostic Tests Performance
Description: Evaluate diagnostic test performance using data from laboratory or diagnostic research. It supports both binary and continuous test variables. It allows users to compute key performance indicators and visualize Receiver Operating Characteristic (ROC) curves, determine optimal cut-off thresholds, display confusion matrix, and export publication-ready plot. It aims to facilitate the application of statistical methods in diagnostic test evaluation by healthcare professionals. The methodology used to compute the performance indicators follows the overview described by Habibzadeh (2025) <doi:10.11613/BM.2025.010101>. Thanks to 'shiny' package.
Author: Nassim AYAD [aut, cre]
Maintainer: Nassim AYAD <nassim.ayad.ph@gmail.com>

Diff between EvalTest versions 1.0.3 dated 2025-10-15 and 1.0.5 dated 2025-11-17

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Package LTFHPlus updated to version 2.2.0 with previous version 2.1.4 dated 2025-05-26

Title: Implementation of LT-FH++
Description: Implementation of LT-FH++, an extension of the liability threshold family history (LT-FH) model. LT-FH++ uses a Gibbs sampler for sampling from the truncated multivariate normal distribution and allows for flexible family structures. LT-FH++ was first described in Pedersen, Emil M., et al. (2022) <doi:10.1016/j.ajhg.2022.01.009> as an extension to LT-FH with more flexible family structures, and again as the age-dependent liability threshold (ADuLT) model Pedersen, Emil M., et al. (2023) <https://www.nature.com/articles/s41467-023-41210-z> as an alternative to traditional time-to-event genome-wide association studies, where family history was not considered.
Author: Emil Michael Pedersen [aut, cre], Florian Prive [aut, ths], Bjarni Johann Vilhjalmsson [ths], Esben Agerbo [ths], Jette Steinbach [aut], Lucas Rasmussen [ctb]
Maintainer: Emil Michael Pedersen <emp@ph.au.dk>

Diff between LTFHPlus versions 2.1.4 dated 2025-05-26 and 2.2.0 dated 2025-11-17

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Package skylight updated to version 1.4 with previous version 1.3 dated 2025-09-24

Title: A Simple Sky Illuminance Model
Description: A tool to calculate sky illuminance values (in lux) for both sun and moon. The model is a translation of the Fortran code by Janiczek and DeYoung (1987) <https://archive.org/details/DTIC_ADA182110>.
Author: Koen Hufkens [aut, cre] , BlueGreen Labs [cph, fnd]
Maintainer: Koen Hufkens <koen.hufkens@gmail.com>

Diff between skylight versions 1.3 dated 2025-09-24 and 1.4 dated 2025-11-17

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New package Romeb with initial version 0.1.2
Package: Romeb
Title: Robust Median-Based Bayesian Growth Curve Modeling
Version: 0.1.2
Description: Implements robust median-based Bayesian growth curve models that handle Missing Completely at Random (MCAR), Missing At Random (MAR), and Missing Not At Random (MNAR) missing-data mechanisms, and allow auxiliary variables. Models are fitted via 'rjags' (interface to 'JAGS') and summarized with 'coda'.
License: GPL-3
URL: https://github.com/DandanTang0/Romeb
BugReports: https://github.com/DandanTang0/Romeb/issues
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: rjags, coda, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
SystemRequirements: JAGS
LazyData: true
LazyDataCompression: xz
Language: en-US
NeedsCompilation: no
Packaged: 2025-11-12 06:27:14 UTC; lynn
Author: Dandan Tang [aut, cre] , Xin Tong [aut]
Maintainer: Dandan Tang <tangdd20@gmail.com>
Repository: CRAN
Date/Publication: 2025-11-17 09:10:02 UTC

More information about Romeb at CRAN
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New package PDEnaiveBayes with initial version 0.2.8
Package: PDEnaiveBayes
Title: Plausible Naive Bayes Classifier Using PDE
Version: 0.2.8
Date: 2025-11-12
Maintainer: Michael Thrun <m.thrun@gmx.net>
Description: A nonparametric, multicore-capable plausible naive Bayes classifier based on the Pareto density estimation (PDE) featuring a plausible approach to a pitfall in the Bayesian theorem covering low evidence cases. Stier, Q., Hoffmann, J., and Thrun, M.C.: "Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naïve Bayes" (2025).
LazyLoad: yes
LazyData: TRUE
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.8), RcppParallel (>= 5.1.4), pracma, plotly, utils, grDevices, stats, graphics, methods, ggplot2, DatabionicSwarm, memshare
Suggests: FCPS(>= 1.3.5), ABCanalysis, modeest, deldir, ScatterDensity (>= 0.1.1), gridExtra, parallelDist, parallel, DataVisualizations (>= 1.1.5)
LinkingTo: Rcpp, RcppParallel
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
BugReports: https://github.com/Mthrun/PDEbayes/issues
Packaged: 2025-11-12 07:13:52 UTC; mct
Author: Michael Thrun [aut, cph, cre] , Quirin Stier [aut, rev] , Tim Robin Neldner [ctr, ctb]
Repository: CRAN
Date/Publication: 2025-11-17 09:10:07 UTC

More information about PDEnaiveBayes at CRAN
Permanent link

Package antaresEditObject updated to version 0.9.3 with previous version 0.9.2 dated 2025-09-24

Title: Edit an 'Antares' Simulation
Description: Edit an 'Antares' simulation before running it : create new areas, links, thermal clusters or binding constraints or edit existing ones. Update 'Antares' general & optimization settings. 'Antares' is an open source power system generator, more information available here : <https://antares-simulator.org/>.
Author: Tatiana Vargas [aut, cre], Frederic Breant [ctb], Victor Perrier [ctb], Baptiste Seguinot [ctb], Benoit Thieurmel [ctb], Titouan Robert [ctb], Jalal-Edine Zawam [ctb], Etienne Sanchez [ctb], Janus De Bondt [ctb], Assil Mansouri [ctb], Abdallah Mahoud [...truncated...]
Maintainer: Tatiana Vargas <tatiana.vargas@rte-france.com>

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Package spatstat.univar updated to version 3.1-5 with previous version 3.1-4 dated 2025-07-12

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

Diff between spatstat.univar versions 3.1-4 dated 2025-07-12 and 3.1-5 dated 2025-11-17

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Package SHELF updated to version 1.12.1 with previous version 1.12.0 dated 2025-03-01

Title: Tools to Support the Sheffield Elicitation Framework
Description: Implements various methods for eliciting a probability distribution for a single parameter from an expert or a group of experts. The expert provides a small number of probability judgements, corresponding to points on his or her cumulative distribution function. A range of parametric distributions can then be fitted and displayed, with feedback provided in the form of fitted probabilities and percentiles. For multiple experts, a weighted linear pool can be calculated. Also includes functions for eliciting beliefs about population distributions; eliciting multivariate distributions using a Gaussian copula; eliciting a Dirichlet distribution; eliciting distributions for variance parameters in a random effects meta-analysis model; survival extrapolation. R Shiny apps for most of the methods are included.
Author: Jeremy Oakley [aut, cre]
Maintainer: Jeremy Oakley <j.oakley@sheffield.ac.uk>

Diff between SHELF versions 1.12.0 dated 2025-03-01 and 1.12.1 dated 2025-11-17

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Package robfilter updated to version 4.1.6 with previous version 4.1.5 dated 2024-07-16

Title: Robust Time Series Filters
Description: Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) <doi:10.1515/BMT.2006.010>. The adaptive online repeated median by Schettlinger et al. (2010) <doi:10.1002/acs.1105> and the slope comparing adaptive repeated median by Borowski and Fried (2013) <doi:10.1007/s11222-013-9391-7> choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) <doi:10.1080/03610910802514972> for a multivariate online adaptive repeated median and Borowski (2012) <doi:10.17877/DE290R-14393> for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter w [...truncated...]
Author: Roland Fried [aut, cre], Karen Schettlinger [aut], Matthias Borowski [aut], Robin Nunkesser [ctb], Thorsten Bernholt [ctb]
Maintainer: Roland Fried <fried@statistik.tu-dortmund.de>

Diff between robfilter versions 4.1.5 dated 2024-07-16 and 4.1.6 dated 2025-11-17

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New package enhancer with initial version 1.1.0
Package: enhancer
Version: 1.1.0
Date: 2025-10-21
Title: Mixed-Effects Models Enhancing Functions
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>
Description: Special functions that enhance other mixed effect model packages by creating overlayed, reduced rank, and reduced model matrices together with multiple data sets to practice the use of these models. For more details see Covarrubias-Pazaran (2016) <doi:10.1371/journal.pone.0156744>.
Depends: R(>= 3.5.0), Matrix (>= 1.0), MASS, methods, crayon
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Repository: CRAN
Suggests: rmarkdown, knitr, orthopolynom, RSpectra, evola, lme4breeding, sommer
NeedsCompilation: no
Packaged: 2025-11-12 02:38:20 UTC; giovannycovarrubias
Date/Publication: 2025-11-17 09:00:02 UTC

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New package ELmethodVar with initial version 0.1
Package: ELmethodVar
Version: 0.1
Date: 2025-11-12
Title: Empirical Likelihood Inference of Variance Components in Linear Mixed-Effects Models
Author: Jingru Zhang [aut, cre]
Maintainer: Jingru Zhang <jrzhang001@gmail.com>
Depends: R (>= 3.5.0)
Description: Provides empirical likelihood-based methods for the inference of variance components in linear mixed-effects models.
License: GPL (>= 2)
URL: https://github.com/jingru-zhang/ELmethod
NeedsCompilation: no
Packaged: 2025-11-12 05:59:57 UTC; jingruzhang
Repository: CRAN
Date/Publication: 2025-11-17 09:00:15 UTC

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New package coFAST with initial version 0.1.0
Package: coFAST
Title: Spatially-Aware Cell Clustering Algorithm with Cluster Significant Assessment
Version: 0.1.0
Date: 2025-11-12
Author: Wei Liu [aut, cre], Xiao Zhang [aut], Yi Yang [aut], Peng Xie [aut], Chengqi Lin [aut], Jin Liu [aut]
Maintainer: Wei Liu <liuweideng@gmail.com>
Description: A spatially-aware cell clustering algorithm is provided with cluster significance assessment. It comprises four key modules: spatially-aware cell-gene co-embedding, cell clustering, signature gene identification, and cluster significant assessment. More details can be referred to Peng Xie, et al. (2025) <doi:10.1016/j.cell.2025.05.035>.
License: GPL-3
Depends: R (>= 4.0.0),
Imports: Rcpp (>= 1.0.10), furrr, future, ggplot2, irlba, DR.SC, PRECAST, ProFAST, Matrix, ade4, progress, pbapply, dplyr, Seurat, stats, utils
LazyData: true
URL: https://github.com/feiyoung/coFAST
BugReports: https://github.com/feiyoung/coFAST/issues
Suggests: knitr, rmarkdown, scater, ggrepel, RANN, grDevices
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-11-12 02:32:59 UTC; 10297
Repository: CRAN
Date/Publication: 2025-11-17 09:00:10 UTC

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Package bage updated to version 0.10.1 with previous version 0.9.8 dated 2025-10-16

Title: Bayesian Estimation and Forecasting of Age-Specific Rates
Description: Fast Bayesian estimation and forecasting of age-specific rates, probabilities, and means, based on 'Template Model Builder'.
Author: John Bryant [aut, cre], Junni Zhang [aut], Bayesian Demography Limited [cph]
Maintainer: John Bryant <john@bayesiandemography.com>

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Package CohortPathways (with last version 0.0.1) was removed from CRAN

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

2025-03-19 0.0.1

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

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

2023-06-18 2.0.0

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Package CohortExplorer (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:

2023-10-23 0.1.0
2023-09-12 0.0.17

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Package CohortAlgebra (with last version 0.3.1) was removed from CRAN

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

2025-02-23 0.3.1
2024-06-04 0.3.0
2024-06-02 0.2.1
2024-01-28 0.2.0
2023-12-08 0.1.0
2023-09-13 0.0.4

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Package xml2 updated to version 1.5.0 with previous version 1.4.1 dated 2025-10-27

Title: Parse XML
Description: Bindings to 'libxml2' for working with XML data using a simple, consistent interface based on 'XPath' expressions. Also supports XML schema validation; for 'XSLT' transformations see the 'xslt' package.
Author: Hadley Wickham [aut], Jim Hester [aut], Jeroen Ooms [aut, cre], Posit Software, PBC [cph, fnd], R Foundation [ctb]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between xml2 versions 1.4.1 dated 2025-10-27 and 1.5.0 dated 2025-11-17

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Package future updated to version 1.68.0 with previous version 1.67.0 dated 2025-07-29

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multisession)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers, etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package dipsaus updated to version 0.3.2 with previous version 0.3.1 dated 2025-04-03

Title: A Dipping Sauce for Data Analysis and Visualizations
Description: Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using the 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
Author: Zhengjia Wang [aut, cre], John Magnotti [ctb] , Xiang Zhang [ctb]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

Diff between dipsaus versions 0.3.1 dated 2025-04-03 and 0.3.2 dated 2025-11-17

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