Wed, 28 Oct 2026

New package tppcm with initial version 0.1.0
Package: tppcm
Title: Step Discriminations for the Two-Parameter Partial Credit Model on Top of 'TAM'
Version: 0.1.0
Description: In the two-parameter partial credit model (TPPCM) of Yu (1991) <https://hdl.handle.net/2142/21459>, every step of a polytomous item has its own discrimination. Estimation is left to existing software: 'TAM' (tam.mml.3pl() with a step design matrix, tam.mml.2pl(), tam.mml()) and, for the bilinear product form and non-negativity constraints, 'sirt' (xxirt()). The package adds what these packages do not provide: standard errors of step discriminations based on the full observed information, step-level Wald tests, and score tests with modification indices and expected parameter changes for moving down the model ladder saturated TPPCM -> product form -> generalized partial credit model -> partial credit model, limited-information fit statistics (the M2 statistic, root mean square error of approximation, standardized root mean squared residual, comparative fit index and Tucker-Lewis index; Maydeu-Olivares and Joe (2006) <doi:10.1007/s11336-005-1295-9>) for any step desig [...truncated...]
License: GPL (>= 2)
URL: https://github.com/jiewenTsai/tppcm
BugReports: https://github.com/jiewenTsai/tppcm/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1), TAM
Imports: CDM, graphics, MASS, sirt, stats
Suggests: knitr, mirt, numDeriv, partykit, psychotools, psychotree, rmarkdown, strucchange, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-16 13:44:45 UTC; jiewentsai
Author: Jie-Wen Tsai [aut, cre]
Maintainer: Jie-Wen Tsai <tsai.jiewen@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:02 UTC

More information about tppcm at CRAN
Permanent link

Package shinyTree updated to version 1.0.0 with previous version 0.3.1 dated 2023-08-07

Title: 'jsTree' Bindings for 'Shiny'
Description: Bindings to 'jsTree' <https://www.jstree.com>, a 'JavaScript' library for interactive trees, to enable rich, editable trees in 'Shiny' applications. Trees can be searched, checked, rearranged, styled and remembered across visits, loaded lazily for very large hierarchies, and built from data frames, 'data.tree' objects or ontologies.
Author: Trestle Technology, LLC [aut], Jeff Allen [aut], Institut de Radioprotection et de Sûrete Nucleaire [cph], Ivan Bozhanov [ctb, cph] , Orange Hill Development [ctb, cph] theme), Accademia di Belle Arti di Urbino [cph] , Mike Schaffer [ctb], Timm Dank [...truncated...]
Maintainer: Michael Bell <bell_michael_a@lilly.com>

Diff between shinyTree versions 0.3.1 dated 2023-08-07 and 1.0.0 dated 2026-10-28

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New package RidgeLRGLH with initial version 0.1.0
Package: RidgeLRGLH
Title: Ridge-Regularized Largest Root Tests for General Linear Hypotheses
Version: 0.1.0
Description: Tests general linear hypotheses in high-dimensional multivariate regression using a ridge-regularized largest root statistic. Estimates the population spectral distribution by linear programming and computes Tracy-Widom centering and scaling constants. Supports fixed, Bayesian, and minimax regularization choices. Implements the methods of Li (2025) <doi:10.48550/arXiv.2504.15510>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: lpSolve, RMTstat, stats
NeedsCompilation: no
Packaged: 2026-10-18 02:07:20 UTC; haoranli
Author: Haoran Li [aut, cre]
Maintainer: Haoran Li <hzl0152@auburn.edu>
Repository: CRAN
Date/Publication: 2026-10-28 10:30:27 UTC

More information about RidgeLRGLH at CRAN
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Package Rduckhts updated to version 2.0.2.0.1.1 with previous version 2.0.1.0.1.0 dated 2026-10-24

Title: 'DuckDB' High Throughput Sequencing File Formats Reader Extension
Description: Bundles the 'duckhts' 'DuckDB' extension for reading High Throughput Sequencing file formats with 'DuckDB'. The 'DuckDB' C extension API <https://duckdb.org/docs/stable/clients/c/api> and its 'htslib' dependency are compiled from vendored sources during package installation. James K Bonfield and co-authors (2021) <doi:10.1093/gigascience/giab007>. VariantKey / RegionKey support follows Nicola Asuni (2018) <doi:10.1101/473744>.
Author: Sounkou Mahamane Toure [aut, cre], Ryan Ward [aut] , Nurture Bio [cph] , James K Bonfield, John Marshall,Petr Danecek ,Heng Li , Valeriu Ohan, Andrew Whitwham,Thomas Keane , Robert M Davies [ctb] , DuckHTS Contributors [cph] ), RBCFTools Authors [cph [...truncated...]
Maintainer: Sounkou Mahamane Toure <sounkoutoure@gmail.com>

Diff between Rduckhts versions 2.0.1.0.1.0 dated 2026-10-24 and 2.0.2.0.1.1 dated 2026-10-28

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New package rd2dnet with initial version 0.1.0
Package: rd2dnet
Title: Boundary Discontinuity Designs on Networks
Version: 0.1.0
Description: Estimation and inference for boundary discontinuity designs on street networks. Extends the location-based framework of 'rd2d' (Cattaneo, Titiunik and Yu, <doi:10.48550/arXiv.2505.07989>) from Euclidean coordinates to network-native coordinates (signed network distance to the boundary and offset along it) and user-defined network metrics (edge costs, travel time, road-class transition penalties, precomputed matrices). Provides side-specific local polynomial estimates of boundary average treatment effect curves with robust bias-corrected inference (Calonico, Cattaneo and Titiunik, 2014, <doi:10.3982/ECTA11757>), uniform confidence bands, weighted and largest aggregate effects, fuzzy designs, covariates, derivative targets, heteroskedasticity-robust, cluster and network Conley (1999, <doi:10.1016/S0304-4076(98)00084-0>) standard errors, a port of the 'rd2d' direct plug-in bandwidth selector, and a network-normalised version of the local polynomial density test of Cattan [...truncated...]
License: GPL-3
URL: https://github.com/zwinship/rd2dnet
BugReports: https://github.com/zwinship/rd2dnet/issues
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, methods, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: dodgr, igraph, knitr, Matrix, osmdata, rmarkdown, sf, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-18 02:06:43 UTC; root
Author: Zach Winship [aut, cre, cph], Matias D. Cattaneo [ctb, cph] , Rocio Titiunik [ctb, cph] , Ruiqi Rae Yu [ctb, cph] , Michael Jansson [ctb, cph] , Xinwei Ma [ctb, cph]
Maintainer: Zach Winship <zachtwinship@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 10:30:08 UTC

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New package PrismR with initial version 1.0.0
Package: PrismR
Title: Pre-Modeling Statistical Audit Framework
Version: 1.0.0
Description: Introduces a statistical validation layer between data preprocessing and predictive modeling. Evaluates the statistical readiness of tabular datasets through data quality assessment, leakage detection, transformation analysis, and feature stability.
License: MIT + file LICENSE
URL: https://arshit-dv.github.io/PrismR/, https://github.com/Arshit-dv/PrismR
BugReports: https://github.com/Arshit-dv/PrismR/issues
Encoding: UTF-8
Imports: graphics, stats, utils, e1071, ggplot2, ggrepel
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-16 12:04:43 UTC; Arshit
Author: Arshit Choudhary [aut, cre, cph], Vanshika Sharma [aut, ctb], Amrit Pal [ths]
Maintainer: Arshit Choudhary <arshitchoudhary3010@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 10:50:17 UTC

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Package likelihood.contr updated to version 0.2.0 with previous version 0.1.1 dated 2026-04-01

Title: Likelihood Contribution Models for Heterogeneous Observation Types
Description: Constructs likelihood models from heterogeneous observation types by composing named contributions. Each observation type (exact, left-censored, right-censored, interval-censored, or custom) contributes independently to the total log-likelihood, which is summed under an i.i.d. assumption. Provides contr_name() for standard R distributions and contr_fn() for user-defined contributions, composed via likelihood_contr() into objects compatible with the likelihood.model inference framework.
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <lex@metafunctor.com>

Diff between likelihood.contr versions 0.1.1 dated 2026-04-01 and 0.2.0 dated 2026-10-28

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New package INLAcircular with initial version 1.0.0
Package: INLAcircular
Title: Bayesian Joint Circular Regression Using 'INLA'
Version: 1.0.0
Description: Provides a Bayesian regression framework for joint models with circular responses and covariates using integrated nested Laplace approximations, following Ye, Van Niekerk and Rue (2026) <doi:10.48550/arXiv.2602.08413>. The package supports link-adjusted von Mises likelihoods, shared latent predictors, structured latent effects, and optional LKJ-based multivariate covariance models. It also provides compiled circular densities and d/p/q/r penalized-complexity priors for von Mises, cardioid, and wrapped Cauchy concentration parameters as developed by Ye, Van Niekerk and Rue (2026) <doi:10.1177/1471082X261453677>.
License: GPL (>= 3)
URL: https://github.com/XiangYEstats/INLAcircular
BugReports: https://github.com/XiangYEstats/INLAcircular/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
LazyData: true
Imports: dplyr, stats, utils
Suggests: circular, graphpcor, INLA (>= 25.08.21), INLAtools, knitr, pkgload, rmarkdown
VignetteBuilder: knitr, rmarkdown
Additional_repositories: https://inla.r-inla-download.org/R/stable
NeedsCompilation: yes
Packaged: 2026-10-18 07:13:45 UTC; xiang
Author: Xiang Ye [aut, cre, cph], Janet Van Niekerk [aut], Haavard Rue [aut, cph], Gerard Jungman [ctb, cph] , Peter John Acklam [ctb]
Maintainer: Xiang Ye <xiang.ye@kaust.edu.sa>
Repository: CRAN
Date/Publication: 2026-10-28 10:40:08 UTC

More information about INLAcircular at CRAN
Permanent link

New package HMMscpg with initial version 1.0.0
Package: HMMscpg
Title: Hidden Markov Models and Shifted Compound Poisson-Gamma Renewal Process
Version: 1.0.0
Imports: Rdpack, methods, stats, utils, Bessel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Description: Provides functions to define, simulate and fit hidden Markov models, hidden semi-Markov models, and their time-varying versions, to incompletely observed point process records. Such data arise when some events of an underlying point process are not recorded or are otherwise missing. The models treat the number of missing events between each pair of consecutively observed events of a point process record as a hidden process. The number of missing events may be fixed or modelled as a random variable whose distribution can vary over time. When the number of missing events is fixed, the observed event times can be modelled as a compound gamma renewal process. When it is random, the observed process is represented by a shifted compound Poisson-gamma renewal process, which may also depend on time, leading to a time-dependent shifted compound Poisson-gamma renewal process. These modelling frameworks are described in detail in Shahzadi, Wang, Parry and Bebbington (2023) <doi:10.1007/s10463- [...truncated...]
License: GPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown, Rmpfr
NeedsCompilation: yes
Packaged: 2026-10-18 05:48:58 UTC; amina
Author: Amina Shahzadi [aut, cre], Ting Wang [aut]
Maintainer: Amina Shahzadi <aminashahzadi@gcu.edu.pk>
Repository: CRAN
Date/Publication: 2026-10-28 10:40:15 UTC

More information about HMMscpg at CRAN
Permanent link

Package gtfstools updated to version 2.0.0 with previous version 1.4.0 dated 2025-01-08

Title: General Transit Feed Specification (GTFS) Editing and Analysing Tools
Description: Utility functions to read, manipulate, analyse and write transit feeds in the General Transit Feed Specification (GTFS) data format.
Author: Daniel Herszenhut [aut] , Rafael H. M. Pereira [aut, cre] , Pedro R. Andrade [aut] , Joao Bazzo [aut] , Mark Padgham [ctb], Christopher Higgins [ctb], Goncalo F. Matos [ctb], Yigit Han Eroglu [ctb], Arthur Bazolli [ctb], Marcus Saraiva [ctb] , Ipea - [...truncated...]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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Package Familia updated to version 2.2.0 with previous version 2.0.0 dated 2026-08-24

Title: 'shiny' Application for Population Structure and Ancestry Assessments
Description: Provides a 'shiny' web application developed by the Breeding Insight team to support pedigree validation and ancestry assessment of plant and animal populations. The app integrates Mendelian error analysis, parentage assignment and genetic composition/ancestry methods to help researchers evaluate genomic relationships through an accessible, web-based interface without requiring command-line tools. Pedigree validation, Mendelian error analysis and parentage assignment build on the 'BIGpopA' package (<https://CRAN.R-project.org/package=BIGpopA>) and support diploid and polyploid data. Genotypes can be uploaded as dosage tables, VCF files, or 'PLINK' .ped files. Ancestry estimation uses the sparse non-negative matrix factorization method of Frichot et al. (2014) <doi:10.1534/genetics.113.160572> as implemented in the 'LEA' package by Frichot and Francois (2015) <doi:10.1111/2041-210X.12382>. Line and breed composition are estimated using the breed composition regression [...truncated...]
Author: Josue Chinchilla-Vargas [aut, cre], Alexander M. Sandercock [aut], Breeding Insight Team [aut]
Maintainer: Josue Chinchilla-Vargas <josue.chinchilla@ufl.edu>

Diff between Familia versions 2.0.0 dated 2026-08-24 and 2.2.0 dated 2026-10-28

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Package controlledburn updated to version 0.3.2 with previous version 0.3.1 dated 2026-10-24

Title: Sparse Geometry Rasterization with Exact Coverage Fractions
Description: Rasterize polygon, line, and point geometry without materializing any pixel values. For polygons it computes exact coverage fractions for polygon-grid intersections, returning sparse tables: run-length encoded interior cells and individually weighted boundary cells. The scanline algorithm is O(perimeter) in both time and memory, using the scan line fill attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>. Exact coverage fractions use the exactextract algorithm by Daniel Baston, vendored from the 'exactextractr' package <doi:10.32614/CRAN.package.exactextractr>. Derived from the 'fasterize' package by Noam Ross.
Author: Michael Sumner [aut, cre] , Noam Ross [aut] , EcoHealth Alliance [cph] , Jim Hester [ctb] , Daniel Baston [cph] ), ISciences, LLC [cph] )
Maintainer: Michael Sumner <mdsumner@gmail.com>

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Package carrier updated to version 0.4.0 with previous version 0.3.0.4 dated 2025-09-11

Title: Isolate Functions for Remote Execution
Description: Sending functions to remote processes can be wasteful of resources because they carry their environments with them. With the carrier package, it is easy to create functions that are isolated from their environment. These isolated functions, also called crates, print at the console with their total size and can be easily tested locally before being sent to a remote.
Author: Lionel Henry [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Lionel Henry <lionel@posit.co>

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New package BayesAiken with initial version 2.0.0
Package: BayesAiken
Title: Bayesian Content Validity Coefficients with Credibility Intervals
Version: 2.0.0
Date: 2026-09-24
Description: Bayesian inference for the six rating coefficients proposed by Aiken (1985) <doi:10.1177/0013164485451012> and Aiken (1989) <doi:10.1177/0013164489492003>: V (content validity), H (homogeneity), C (congruence), R (repeatability), A (rater agreement) and I (item coherence). All six are expressed as functionals of the population distribution of rating categories, so a single Dirichlet-Multinomial model yields their full posterior by push-forward. This treats each judge as one categorical observation and avoids the pseudo-replication of Beta-Binomial formulations. R is modelled on the c-by-c joint table because it is not a functional of the marginal distribution. Provides classical estimates with the correct parity correction, highest density and equal-tailed credibility intervals, posterior threshold probabilities, prior sensitivity analysis and a friendly step-by-step verbose report.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), shiny, readxl, writexl, openxlsx
URL: https://github.com/jventural/BayesAiken
BugReports: https://github.com/jventural/BayesAiken/issues
NeedsCompilation: no
Packaged: 2026-10-16 13:21:58 UTC; PC
Author: Jose Ventura-Leon [aut, cre]
Maintainer: Jose Ventura-Leon <jventuraleon@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:18 UTC

More information about BayesAiken at CRAN
Permanent link

Package aqp updated to version 2.3.3 with previous version 2.3.2 dated 2026-04-30

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilD [...truncated...]
Author: Dylan Beaudette [aut, cre] , Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb], Stephen Roecker [aut, ctb], David Rossiter [ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

Diff between aqp versions 2.3.2 dated 2026-04-30 and 2.3.3 dated 2026-10-28

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New package aidR with initial version 0.2.4
Package: aidR
Title: Reading and Standardizing Automated Insulin Delivery Data
Version: 0.2.4
Description: Parses the native exports of several automated insulin delivery (AID) platforms into a common, platform-independent format for continuous glucose monitoring (CGM), basal, bolus, carbohydrate, and self-monitored blood glucose (SMBG) data. Additional functions check completeness, filter, produce visualizations, and convert the data to other formats.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: readxl, tools, dplyr, lubridate, rjson, tidyr, stringr, utils, rlang, stats, graphics, iglu, hms
Suggests: knitr, rmarkdown, cgmquantify, ggplot2, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://github.com/madleina/aidR
BugReports: https://github.com/madleina/aidR/issues
NeedsCompilation: no
Packaged: 2026-10-16 12:43:03 UTC; madleina
Author: Madleina Caduff [aut, cre] , Aritz Lizoain [aut] , Diabetes Center Berne [cph, fnd]
Maintainer: Madleina Caduff <madleina.caduff@dcberne.com>
Repository: CRAN
Date/Publication: 2026-10-28 11:00:09 UTC

More information about aidR at CRAN
Permanent link

Package washr updated to version 1.2.0 with previous version 1.1.0 dated 2026-09-02

Title: Publication Toolkit for Water, Sanitation and Hygiene (WASH) Data
Description: A toolkit to set up an R data package in a consistent structure. Automates tasks like tidy data export, data dictionary documentation, README and website creation, and citation management.
Author: Mian Zhong [aut] , Margaux Goetschmann [aut] , Colin Walder [aut] , Lars Schoebitz [aut, cre] , Global Health Engineering, ETH Zurich [cph]
Maintainer: Lars Schoebitz <lschoebitz@ethz.ch>

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Package thisutils updated to version 0.5.3 with previous version 0.5.0 dated 2026-08-21

Title: Reliable Utilities for Reusable Research Workflows
Description: Provides reusable building blocks for research packages across matrix representation, numerical computation, neighborhood evaluation, controlled execution, and runtime interoperability. Core tools preserve declared sparse semantics, expose dense-memory and output boundaries, standardize neighborhood and classification results, and align serial and parallel result and error behavior. Additional helpers support structured messages, optional dependency checks, and common statistical workflows.
Author: Meng Xu [aut, cre] , Haoliang Zhu [aut]
Maintainer: Meng Xu <mengxu98@qq.com>

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Package spinebil updated to version 1.0.6 with previous version 1.0.5 dated 2025-10-17

Title: Investigating New Projection Pursuit Index Functions
Description: Projection pursuit is used to find interesting low-dimensional projections of high-dimensional data by optimizing an index over all possible projections. The 'spinebil' package contains methods to evaluate the performance of projection pursuit index functions using tour methods. A paper describing the methods can be found at <doi:10.1007/s00180-020-00954-8>.
Author: Ursula Laa [aut] , Dianne Cook [aut] , Tina Rashid Jafari [aut, cre]
Maintainer: Tina Rashid Jafari <tina.rashidjafari@gmail.com>

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Package glmnet updated to version 5.2 with previous version 5.1 dated 2026-09-24

Title: Lasso and Elastic-Net Regularized Generalized Linear Models
Description: Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped multinomial regression; see <doi:10.18637/jss.v033.i01> and <doi:10.18637/jss.v039.i05>. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family (<doi:10.18637/jss.v106.i01>). This comes with a modest computational cost, so when the built-in families suffice, they should be used instead. The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers cited.
Author: Jerome Friedman [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [aut], Kenneth Tay [aut], Noah Simon [aut], Junyang Qian [ctb], James Yang [aut], Jonathan Taylor [aut]
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package discoCVI updated to version 0.2.1 with previous version 0.2.0 dated 2026-10-27

Title: Implementation of the DISCO Metric for Internal Clustering Evaluation
Description: Implementation of the DISCO (Density-based Internal Score for Clusterings with nOise) metric, a cluster validity index for evaluating density-based clustering results without ground truth labels. DISCO is the first index to explicitly assess the quality of noise point assignments in addition to cluster quality. It uses density-connectivity distance derived from a minimum spanning tree of the mutual-reachability graph, providing interpretable, bounded scores in [-1, 1]. Higher scores indicate better clustering. Based on Beer et al. (2025) <doi:10.48550/arXiv.2503.00127>.
Author: Amin Entezari [aut, cre] , Davide Chicco [ctb] , Anna Beer [aut] ), Lena Krieger [aut] ), Pascal Weber [aut] )
Maintainer: Amin Entezari <amin_entezari@outlook.com>

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Package wsMed updated to version 1.2.0 with previous version 1.1.0 dated 2026-09-18

Title: Within-Subject Mediation Analysis Using Structural Equation Modeling
Description: Within-subject mediation analysis using structural equation modeling. Examine how changes in an outcome variable between two conditions are mediated through one or more variables. Supports within-subject mediation analysis using the 'lavaan' package by Rosseel (2012) <doi:10.18637/jss.v048.i02>, and extends Monte Carlo confidence interval estimation to missing data scenarios using the 'semmcci' package by Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.
Author: Wendie Yang [aut, cre] , Shu Fai Cheung [aut]
Maintainer: Wendie Yang <1581075494q@gmail.com>

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Package thisplot updated to version 0.4.6 with previous version 0.4.3 dated 2026-08-01

Title: Utility Functions for Plotting
Description: Provides utility functions for plotting. Includes functions for color manipulation, plot customization, panel size control, data optimization for plots, and layout adjustments.
Author: Meng Xu [aut, cre] , Haoliang Zhu [aut]
Maintainer: Meng Xu <mengxu98@qq.com>

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Package CompositionalSR updated to version 1.5 with previous version 1.4 dated 2026-04-14

Title: Spatial Regression Models with Compositional Data
Description: Spatial and non-spatial regression models with compositional responses (and compositional predictors) using the alpha--transformation. Relevant papers include: Tsagris M. and Pantazis Y. (2026), <doi:10.48550/arXiv.2510.12663>, Tsagris M. (2015), <https://soche.cl/chjs/volumes/06/02/Tsagris(2015).pdf>, Tsagris M.T., Preston S. and Wood A.T.A. (2011), <doi:10.48550/arXiv.1106.1451>.
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package cna updated to version 4.1.0 with previous version 4.0.3 dated 2025-06-02

Title: Causal Modeling with Coincidence Analysis
Description: Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2020) <doi:10.1017/psrm.2018.45>. CNA is designed to recover INUS-causation from data, which is particularly relevant for analyzing processes featuring conjunctural causation (component causation) and equifinality (alternative causation). CNA is currently the only method for INUS-discovery that allows for multiple effects (outcomes/endogenous factors), meaning it can analyze common-cause and causal chain structures. Moreover, as of version 4.0, it is the only method of its kind that provides measures for model evaluation and selection that are custom-made for the problem of INUS-discovery.
Author: Mathias Ambuehl [aut, cre, cph], Michael Baumgartner [aut, cph], Ruedi Epple [ctb], Veli-Pekka Parkkinen [ctb], Alrik Thiem [ctb]
Maintainer: Mathias Ambuehl <mathias.ambuehl@consultag.ch>

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Package likelihood.model updated to version 1.0.2 with previous version 1.0.1 dated 2026-05-24

Title: Likelihood-Based Statistical Inference in the Fisherian Tradition
Description: Facilitates building likelihood models in the Fisherian tradition following Richard Royall (1997, ISBN:978-0412044113) "Statistical Evidence: A Likelihood Paradigm". Defines generic methods for working with likelihoods (loglik(), score(), hess_loglik(), fim()) and provides functions for pure likelihood-based inference (support(), relative_likelihood(), likelihood_interval(), profile_loglik()).
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <lex@metafunctor.com>

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Package flexhaz updated to version 0.5.3 with previous version 0.5.2 dated 2026-05-23

Title: Dynamic Failure Rate Distributions for Survival Analysis
Description: Flexible framework for specifying survival distributions through their hazard (failure rate) functions. Define arbitrary time-varying hazard functions to model complex failure patterns including bathtub curves, proportional hazards with covariates, and other non-standard hazard behaviors. Provides automatic computation of survival, CDF, PDF, quantiles, and sampling. Implements the likelihood model interface for maximum likelihood estimation with right-censored and left-censored survival data.
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <queelius@gmail.com>

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Package compositional.mle updated to version 2.0.1 with previous version 2.0.0 dated 2026-03-19

Title: Compositional Maximum Likelihood Estimation
Description: Provides composable optimization strategies for maximum likelihood estimation (MLE). Solvers are first-class functions that combine via sequential chaining, parallel racing, and random restarts. Implements gradient ascent, Newton-Raphson, quasi-Newton (BFGS), and derivative-free methods with support for constrained optimization and tracing. Returns 'mle' objects compatible with 'algebraic.mle' for downstream analysis. Methods based on Nocedal J, Wright SJ (2006) "Numerical Optimization" <doi:10.1007/978-0-387-40065-5>.
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <queelius@gmail.com>

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Package algebraic.mle updated to version 2.0.3 with previous version 2.0.2 dated 2026-03-19

Title: Algebraic Maximum Likelihood Estimators
Description: The maximum likelihood estimator (MLE) is a technology: under regularity conditions, any MLE is asymptotically normal with variance given by the inverse Fisher information. This package exploits that structure by defining an algebra over MLEs. Compose independent estimators into joint MLEs via block-diagonal covariance ('joint'), optimally combine repeated estimates via inverse-variance weighting ('combine'), propagate transformations via the delta method ('rmap'), and bridge to distribution algebra via conversion to normal or multivariate normal objects ('as_dist'). Supports asymptotic ('mle', 'mle_numerical') and bootstrap ('mle_boot') estimators with a unified interface for inference: confidence intervals, standard errors, AIC, Fisher information, and predictive intervals. For background on maximum likelihood estimation, see Casella and Berger (2002, ISBN:978-0534243128). For the delta method and variance estimation, see Lehmann and Casella (1998, ISBN:978-0387985022).
Author: Alexander Towell [aut, cre]
Maintainer: Alexander Towell <lex@metafunctor.com>

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

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

2024-11-26 1.0.1
2024-01-19 1.0.0

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Package dynutils updated to version 1.0.13 with previous version 1.0.12 dated 2025-09-02

Title: Common Functionality for the 'dynverse' Packages
Description: Provides common functionality for the 'dynverse' packages. 'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods. For more information, check out <https://dynverse.org>.
Author: Robrecht Cannoodt [aut, cre] , Wouter Saelens [aut]
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

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Package enrichit updated to version 0.2.7 with previous version 0.2.6 dated 2026-10-06

Title: 'C++' Implementations of Functional Enrichment Analysis
Description: Fast implementations of functional enrichment analysis methods using 'C++' via 'Rcpp'. Currently provides Over-Representation Analysis (ORA), Gene Set Enrichment Analysis (GSEA), design-aware GSEA on RNA-seq counts with per-sample gene set scoring, Weighted Enrichment Analysis for ORA and GSEA, Network-based Set Enrichment Analysis (NSEA), multi-layer network-based enrichment, and multi-omics integration workflows. Additional features include early fusion at the feature level, late fusion at the pathway level, multi-omics contribution tracing, topology-aware explanation helpers, Bayesian term selection, and extremely fast Random Walk with Restart (RWR) using 'RcppEigen'. The enrichment methods build on GSEA by Subramanian et al. (2005) <doi:10.1073/pnas.0506580102>, the multilevel strategy derived from 'fgsea' by Korotkevich et al. (2021) <doi:10.1101/060012>, and network-based enrichment ideas described by Glaab et al. (2012) <doi:10.1093/bioinformatics/bts389>.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between enrichit versions 0.2.6 dated 2026-10-06 and 0.2.7 dated 2026-10-28

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