cran.r-universe.dev

[cran] jmdem 1.0.2

karlwuky@suss.edu.sg (Ka Yui Karl Wu) — Sun, 06 Sep 2026 17:09:18 GMT

Joint mean and dispersion effects models fit the mean and dispersion parameters of a response variable by two separate linear models, the mean and dispersion submodels, simultaneously. It also allows the users to choose either the deviance or the Pearson residuals as the response variable of the dispersion submodel. Furthermore, the package provides the possibility to nest the submodels in one another, if one of the parameters has significant explanatory power on the other. Wu & Li (2016) .

[cran] BKT 0.1.2

yuanyuhaoapply@163.com (Yuhao Yuan) — Sat, 05 Sep 2026 16:20:19 GMT

Fitting, cross-validating, and predicting with Bayesian Knowledge Tracing (BKT) models. It is designed for analyzing educational datasets to trace student knowledge over time. The package includes functions for fitting BKT models, evaluating their performance using various metrics, and making predictions on new data. It provides functionality similar to the 'Python' package 'pyBKT' authored by Zachary A. Pardos (zp@berkeley.edu) at .

[cran] Rmalschains 0.2-12

c.bergmeir@decsai.ugr.es (Christoph Bergmeir) — Sat, 05 Sep 2026 16:10:09 GMT

An implementation of an algorithm family for continuous optimization called memetic algorithms with local search chains (MA-LS-Chains), as proposed in Molina et al. (2010) and Molina et al. (2011) . Rmalschains is further discussed in Bergmeir et al. (2016) . Memetic algorithms are hybridizations of genetic algorithms with local search methods. They are especially suited for continuous optimization.

[cran] qdaR 0.1.0

fre.ms@fre.ms (fre.ms) — Sat, 05 Sep 2026 13:50:08 GMT

Reads the versioned exchange files written by the Zotero plugins 'zotQDA' and 'qdaZ' -- coded fragments, code systems, coding histories and team-consensus results -- validates them against the shipped contract, and reproduces the plugin's graphics with 'ggplot2'. Adds what those plugins deliberately leave out: six agreement coefficients with bootstrap confidence intervals, the reliability of the segmentation itself, chi-squared tests of code by group tables with effect sizes, correspondence analysis, multidimensional scaling and hierarchical clustering of codes. Projects from other programs can be read through the 'REFI-QDA' interchange standard , which makes those analyses available to users of established software that does not offer them; the subset a '.qdpx' supports is reported on import. Reference files are included, so every function can be tried without a Zotero installation.

[cran] rregm 1.4

dgallardo@ubiobio.cl (Diego Gallardo) — Sat, 05 Sep 2026 04:40:26 GMT

Provides estimation and data generation tools for several new regression models, including the gamma, beta, inverse gamma, beta prime, log-normal and log-logistic distributions. These models can be parameterized based on the mean, median, mode, geometric mean and harmonic mean, except for the log-logistic model which is based on alternative parametrizations. For details, see Bourguignon and Gallardo (2025a) and Bourguignon and Gallardo (2025b) . The package also implements higher-order likelihood inference through Skovgaard-adjusted likelihood ratio statistics and predictive shrinkage estimators reparameterized beta regression models.

[cran] plotomics 0.1.0

samuelbharti.io@gmail.com (Samuel Bharti) — Fri, 04 Sep 2026 21:50:02 GMT

Lightweight, GPU-accelerated bioinformatics visualization widgets (volcano plots, expression and clustered heatmaps, dot plots, stacked violins, embeddings, spatial tissue maps, oncoprints, protein domain lollipops, Kaplan-Meier curves, mutational signature profiles, UpSet plots, treemaps, networks and Hi-C contact matrices) backed by a shared JavaScript core and exposed to R through 'htmlwidgets'. Designed for large datasets that render smoothly in the browser, the 'RStudio' Viewer, R Markdown, Quarto and Shiny.

[cran] MergeKmeans 0.3.0

donga2@erau.edu (Aqi Dong) — Fri, 04 Sep 2026 18:29:18 GMT

Fast clustering of large datasets by hierarchically merging components of a K-means solution based on the pairwise overlap between the Gaussian mixture components implied by the K-means partition, as proposed by Melnykov and Michael (2020) . Implements the DEMP-K merging algorithm with single, Ward's, average, and complete linkages, the overlap map display for selecting the number of clusters, four K-means variants corresponding to Gaussian mixtures with spherical or elliptical, homoscedastic or heteroscedastic components, and a tool for selecting the number of K-means components.

[cran] rlas 1.9.5

info@r-lidar.com (Jean-Romain Roussel) — Fri, 04 Sep 2026 14:25:30 GMT

Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing . The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 .

[cran] crops 1.0.4

dan.grose@lancaster.ac.uk (Daniel Grose) — Fri, 04 Sep 2026 13:50:01 GMT

Implements the Changepoints for a Range of Penalties (CROPS) algorithm of Haynes et al. (2017) for finding all of the optimal segmentations for multiple penalty values over a continuous range.

[cran] esviz 0.0.4

ariadna.batalla@bsc.es (Ariadna Batalla) — Fri, 04 Sep 2026 13:20:02 GMT

A plotting package for climate science and services. Provides a set of functions for visualizing climate data, including maps, time series, scorecards and other diagnostics. Some functions are adapted and extended from the 's2dv' and 'CSTools' packages (Manubens et al. (2018) ; Pérez-Zanón et al. (2022) ), with more consistent and integrated functionalities.

[cran] trend 1.1.8

thorsten.pohlert@gmx.de (Thorsten Pohlert) — Thu, 03 Sep 2026 14:40:02 GMT

The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.

[cran] prevtoinc 0.12.1

willrichn@rki.de (Niklas Willrich) — Thu, 03 Sep 2026 14:39:33 GMT

Functions to simulate point prevalence studies (PPSs) of healthcare-associated infections (HAIs) and to convert prevalence to incidence in steady state setups. Companion package to the preprint Willrich et al., From prevalence to incidence - a new approach in the hospital setting; , where methods are explained in detail.

[cran] biohttp 0.1.2

samuelbharti.io@gmail.com (Samuel Bharti) — Thu, 03 Sep 2026 14:38:24 GMT

Web service calls return a normalized result value instead of raising a condition, so a caller branches on data rather than on an error handler. Transport failure, a non-success status code, and an unreadable response body are reported as three distinct outcomes. Per-host circuit breaking, retry with a transient-failure predicate, optional throttling, redacted request headers, and a success-only cache come as defaults. Many questions to one source can be asked as a single batch, where only the entries the cache is missing reach the network. Service-specific knowledge is left to the client packages built on top. The circuit breaker is the pattern described in Nygard (2018, ISBN:9781680502398).

[cran] PTLENKies 0.1.0

otodjitheodule@gmail.com (Théophile Otodji) — Thu, 03 Sep 2026 14:38:10 GMT

Implements statistical tools for analyzing, simulating, and computing properties of the Power Topp Leone Exponential Negative Kies Burr (PTLENKBurr). See Atchadé M, Otodji T, and Djibril A (2024) and Atchadé M, Otodji T, Djibril A, and N'bouké M (2023) for details.

[cran] later2 0.1

m.vargas.sepulveda@gmail.com (Mauricio Vargas Sepulveda) — Thu, 03 Sep 2026 12:50:02 GMT

Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied. The functions are scheduled in an event loop. This is a derived work from the 'later' package aiming to reduce the number of dependencies.

[cran] Compositionalasmr 1.0

mtsagris@uoc.gr (Michail Tsagris) — Thu, 03 Sep 2026 12:20:27 GMT

The alpha-spatial median regression is performed via the iteretively reweighted least squares algorithm. At first the alpha-transformation of Tsagris, Preston and Wood (2011) is applied and then the non-linear regression model is fitted.

[cran] SCCDdesign 0.1.0

vyshnaic@gmail.com (Vyshna I C) — Thu, 03 Sep 2026 12:20:22 GMT

Provides functions for constructing screening designs for experiments involving three-level continuous and two-level categorical factors. The package implements three methods proposed by Jones, B., Lekivetz, R., Majumdar, D. and Nachtsheim, C. (2025) for generating efficient screening designs for even run sizes. It also includes functions for constructing conference matrices using Paley Type I and Type II constructions, as well as construction of pseudo conference matrices by coordinate exchange algorithm given by Jones, B. and Nachtsheim, C. J. (2011) which are used in the development of these screening designs.

[cran] mlr3automl 0.1.0

marcbecker@posteo.de (Marc Becker) — Thu, 03 Sep 2026 12:20:03 GMT

Flexible automated machine learning (AutoML) system for the 'mlr3' ecosystem. Automatically selects a suitable machine learning algorithm and tunes its hyperparameters for a given task. Constructs preprocessing pipelines with multiple parallel branches using 'mlr3pipelines' and jointly optimizes them together with the learners using 'mlr3tuning'. The optimization is driven by asynchronous decentralized Bayesian optimization by Egele et al. (2023) .

[cran] wishartinference 0.1.0

hshi1@swarthmore.edu (Hanqi Shi) — Thu, 03 Sep 2026 12:10:02 GMT

Posterior inference for the shape parameter alpha and mean matrix mu in the model X_i ~ Wishart_p(2*alpha, Sigma), under both an improper prior and a proper Gamma/inverse-Wishart prior. The posterior mode is found via a Newton-within-EM algorithm and joint samples are drawn via rejection sampling.

[cran] MN 1.2

mtsagris@uoc.gr (Michail Tsagris) — Thu, 03 Sep 2026 09:56:49 GMT

Density computation, random matrix generation, maximum likelihood estimation, and regression for the matrix normal distribution. References: Pocuca N., Gallaugher M. P., Clark K. M. & McNicholas P. D. (2019). Assessing and Visualizing Matrix Variate Normality. and the relevant wikipedia page.

[cran] pathling 9.9.0

pathling@csiro.au ("Australian e-Health Research Centre, CSIRO") — Thu, 03 Sep 2026 04:00:02 GMT

R API for 'Pathling', a tool for querying and transforming electronic health record data that is represented using the 'Fast Healthcare Interoperability Resources' (FHIR) standard - see .

[cran] sphereclust 1.1

mtsagris@uoc.gr (Michail Tsagris) — Wed, 02 Sep 2026 18:10:03 GMT

Model based clustering with spherical data using mixtures of elliptically symmetric distributions, namely mixtures of spherical elliptically symmetric projected Cauchy (SESPC) or mixtures of elliptically symmetric angular Gaussian (ESAG) distributions. The relevant paper is: Perdikis T., Alharbi N. and Tsagris M. (2026). .

[cran] flexsynth 0.2.1

lauyeehow1986@gmail.com (Yee How Lau) — Wed, 02 Sep 2026 14:36:06 GMT

Generates utility-oriented synthetic data for supported flat, nested, longitudinal and tree-linked multi-table designs, including patients, admissions, procedures and laboratory results linked by identifiers. The default engine uses sequential conditional synthesis; an opt-in differentially private engine implements person-level (epsilon, delta) mechanisms and records their budget accounting. Synthetic output is not anonymisation. Empirical utility and disclosure-risk diagnostics are descriptive and do not by themselves establish that a release is safe.

[cran] ExperimentalDesignGeneratorandRandomiser 0.1.0

phonics-tiffs1i@icloud.com (BiologyAutomation) — Wed, 02 Sep 2026 14:34:05 GMT

Native R implementation of 'EDGAR', the Experimental Design Generator and Randomiser. 'EDGAR' was originally developed as a suite of 'Excel' workbooks by the Biometrics team at Rothamsted Research . The algorithms were subsequently re-implemented in the open-source 'Python' project 'rotsl/edgar' , distributed as the 'edgar-design' package on 'PyPI' . This R package is a native R port of that 'Python' implementation: it does not require 'Python', 'reticulate' , or any external service at runtime, and provides deterministic, reproducible randomisation for nine experimental designs including alpha designs (Patterson and Williams, 1976) . Cross-language reproducibility with the 'Python' implementation is achieved by porting the Mersenne Twister seeding implementation from 'CPython' and the Fisher-Yates shuffle to native R.

[cran] Directional 7.8

mtsagris@uoc.gr (Michail Tsagris) — Wed, 02 Sep 2026 14:34:02 GMT

A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include: a) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. . b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. . c) Paine J.P., Preston S.P., Tsagris M. and Wood A.T.A. (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. . d) Tsagris M. and Alenazi A. (2024). "An investigation of hypothesis testing procedures for circular and spherical mean vectors". Communications in Statistics-Simulation and Computation, 53(3): 1387--1408. . e) Yu Z. and Huang X. (2024). A new parameterization for elliptically symmetric angular Gaussian distributions of arbitrary dimension. Electronic Journal of Statistics, 18(1): 301--334. . f) Tsagris M. and Alzeley O. (2025). "Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling". Australian & New Zealand Journal of Statistics, 67(1): 77--103. . g) Tsagris M., Papastamoulis P. and Kato S. (2025). "Directional data analysis: spherical Cauchy or Poisson kernel-based distribution". Statistics and Computing, 35:51. . h) Alzeley O. and Tsagris (2026). "On the generalized circular projected Cauchy distribution". Mathematics, 14(11): 1934. .

[cran] ltgsmd 0.2.2

nakamura@miyazaki-u.ac.jp (Daiki Nakamura) — Wed, 02 Sep 2026 11:30:09 GMT

Implements the latent true-score and target-population anchored geometric standardized mean difference (LTG-SMD) framework for two-group effect-size analysis. Provides plug-in estimation, analytic delta-method confidence intervals using a sample fourth-moment plug-in, bias-corrected and bias-corrected-accelerated nonparametric bootstrap confidence intervals with study x group stratification, denominator-sensitivity profiles, and multi-site meta-analytic wrappers. Includes denominator-diagnostic reporting, a pluggable reliability estimator interface, and an explicit interface for specifying the target reference distribution. Companion software to the methodological paper "The Denominator Chooses the Estimand: A Target-Population True-Score Framework for Standardized Mean Differences" (Nakamura, in press, Psychological Methods).

[cran] AdsorpR 0.1.1

j.mandal2@salford.ac.uk (Jajati Mandal) — Wed, 02 Sep 2026 11:10:14 GMT

Model adsorption behavior using classical isotherms, including Langmuir, Freundlich, Brunauer–Emmett–Teller (BET), and Temkin models. The package supports parameter estimation through both linearized and non-linear fitting techniques and generates high-quality plots for model diagnostics. It is intended for environmental scientists, chemists, and researchers working on adsorption phenomena in soils, water treatment, and material sciences. Functions are compatible with base 'R' and 'ggplot2' for visualization.

[cran] TPEA 3.1.1

jiangwei@hrbmu.edu.cn (Wei Jiang) — Wed, 02 Sep 2026 09:30:11 GMT

We described a novel Topology-based pathway enrichment analysis, which integrated the global position of the nodes and the topological property of the pathways in Kyoto Encyclopedia of Genes and Genomes Database. We also provide some functions to obtain the latest information about pathways to finish pathway enrichment analysis using this method.

[cran] PINSPlus 2.0.10

dvp0001@wayne.edu (Van-Dung Pham) — Wed, 02 Sep 2026 05:20:42 GMT

Provides a robust approach for omics data integration and disease subtyping. PINSPlus is fast and supports the analysis of large datasets with hundreds of thousands of samples and features. The software automatically determines the optimal number of clusters and then partitions the samples in a way such that the results are robust against noise and data perturbation (Nguyen et al. (2019) , Nguyen et al. (2017), Nguyen et al. (2021)).

[cran] xtdml 0.1.13

apolselli.econ@gmail.com (Annalivia Polselli) — Tue, 01 Sep 2026 19:10:02 GMT

The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) . 'xtdml' follows the object-oriented architecture of 'DoubleML' (Bach et al., 2024) and uses the 'mlr3' ecosystem.

[cran] getaca 0.1.6

gilles.colling051@gmail.com (Gilles Colling) — Tue, 01 Sep 2026 15:00:32 GMT

Declares, retrieves, verifies, tracks and actively manages external data dependencies too large or too fast-moving to ship inside a package. Resources are identified by package, name and version, pinned to a Secure Hash Algorithm (SHA-256) checksum, and resolved through an explicit policy so that the same installed package always resolves the same bytes. A registry served from a remote host may be signed with Ed25519 and verified against a key the declaring package ships, so the declaration and the key that vouches for it arrive by different routes. Hashing follows National Institute of Standards and Technology (2015) "Secure Hash Standard" ; signing follows Bernstein, Duif, Lange, Schwabe and Yang (2012) "High-Speed High-Security Signatures" and Josefsson and Liusvaara (2017) "Edwards-Curve Digital Signature Algorithm (EdDSA)" . Designed for reproducible offline use and graceful behaviour during package checks.

[cran] FitVerse 1.0-1

karuna.reddy@auckland.ac.nz (Karuna G. Reddy) — Tue, 01 Sep 2026 14:20:02 GMT

Provides a unified, user-friendly interface for fitting parametric probability distributions to continuous univariate data. 'FitVerse' supports 52 distribution families spanning symmetric, right-skewed, heavy-tailed, bounded, and extreme-value shapes, and three estimation methods: Maximum Likelihood Estimation (MLE), Method of Moments (MOM), and L-Moments (L-MOM). Automatic best-fit selection is performed using AIC, BIC, and goodness-of-fit tests (Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises (CvM)). Every fitted model produces a publication-quality diagnostic plot: a histogram overlaid with the fitted density curve and the estimated PDF formula annotated directly on the figure. An optional interactive version is produced via 'plotly'. Additional tools include bootstrap confidence intervals for parameter estimates and return levels, batch fitting across multiple columns for automated workflows and web-upload use cases, JSON serialisation for integration with 'Shiny' web applications, and automated HTML/PDF report generation. 'FitVerse' is designed to support data characterisation in survey sampling, hydrology, and actuarial workflows, where identifying the underlying distribution of a variable is a prerequisite for downstream modelling and inference. L-moment estimation follows Hosking (1990) and Hosking and Wallis (1997, ISBN:9780521430456). Model selection via AIC follows Akaike (1974) and via BIC follows Schwarz (1978) . Bootstrap confidence intervals follow Efron and Hastie (2016, ISBN:9781107149892).

[cran] nlme 3.1-171

r-core@r-project.org (R Core Team) — Tue, 01 Sep 2026 12:37:54 GMT

Fit and compare Gaussian linear and nonlinear mixed-effects models.

[cran] poisFErobust 2.0.1

enwright@umich.edu (Evan Wright) — Tue, 01 Sep 2026 10:15:30 GMT

Computation of robust standard errors of Poisson fixed effects models, following Wooldridge (1999).

[cran] confidenceSim 0.1.1

freda.werdiger@unimelb.edu.au (Freda Werdiger) — Tue, 01 Sep 2026 10:15:14 GMT

Simulate one or many frequentist confidence clinical trials based on a specified set of parameters. From a two-arm, single-stage trial to a perpetually run Adaptive Platform Trial, this package offers vast flexibility to customize your trial and observe operational characteristics over thousands of instances.

[cran] ggalttext 0.4.0

joseph@ysunflower.com (Joseph Barbier) — Mon, 31 Aug 2026 20:14:02 GMT

Generates concise alternative text for data visualizations created with 'ggplot2'. Descriptions are produced by inspecting plot layers, labels, scales, and facets, with support for multiple languages and alternative text stored in plot metadata.

[cran] epoxy 1.0.1

garrick@adenbuie.com (Garrick Aden-Buie) — Mon, 31 Aug 2026 20:13:44 GMT

Extra strength 'glue' for data-driven templates. String interpolation for 'Shiny' apps or 'R Markdown' and 'knitr'-powered 'Quarto' documents, built on the 'glue' and 'whisker' packages.

[cran] OptOTrials 1.0.3

yeonheepark@skku.edu (Yeonhee Park) — Mon, 31 Aug 2026 20:12:54 GMT

Functions to design and simulate optimal two-stage randomized controlled trials (RCTs) with ordered categorical outcomes, supporting rank-based tests and group-sequential decision rules. Methods build on classical and modern rank tests and two-stage/Group-Sequential designs, e.g., Park (2025) . The functions 'rule()', 'op()' and 'design_table()' provide a single entry point for constructing designs, evaluating their operating characteristics, and tabulating several designs at once. The earlier functions, one for each combination of test statistic and stopping rule, are retained and still return the same values, but they are deprecated: each warns and names its replacement, and they will be removed in the next version. Please see the package reference manual and the vignette for details.

[cran] rdborrow 0.0.4.0

secrmatt@gmail.com (Matt Secrest) — Mon, 31 Aug 2026 14:00:10 GMT

Implements causal inference methods for incorporating external control data into randomized controlled trials (RCTs) with longitudinal outcomes. Provides an analysis module supporting weighting-based methods such as inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW), difference-in-differences (DID), and synthetic control approaches for borrowing external control information, as well as a simulation module for generating trial and external control data, evaluating estimator performance via Monte Carlo studies, and conducting power analyses for sample size determination. Methods are based on Zhou et al. (2024) and Zhou et al. (2024) .

[cran] PropTestR 1.0.0

vinodhkumar.rajendran@gmail.com (Vinodhkumar Obli Rajendran) — Mon, 31 Aug 2026 12:30:08 GMT

Unified methods for comparing two independent or paired proportions. Provides classical, exact, score-based, non-inferiority, equivalence, effect-size, confidence-interval, and stratified procedures with standardized publication-ready output. Farrington-Manning inference is supported through established score-based methods described by Farrington and Manning (1990) and implemented through 'ratesci', while additional established methods are provided through 'DescTools' and base R.

[cran] stow 0.3.0

cole@colebrokamp.com (Cole Brokamp) — Sun, 30 Aug 2026 13:01:38 GMT

Turns remote file URLs into paths to durable managed local copies stored in a fixed subdirectory of platform-appropriate, package-specific user data directories. Matching copies are reused across R sessions and remain available for offline use. Supports optional ETag-based versions, content validation, and staged replacement that prevents failed downloads and files that fail a supplied validator from becoming managed local copies. Includes tools to inspect, conservatively prune, and explicitly remove retained copies.

[cran] mziln 1.0

mtsagris@uoc.gr (Michail Tsagris) — Sun, 30 Aug 2026 13:01:18 GMT

A multivariate zero inflated logistic normal regression model is implemented for compositional data with zero values present. The relevant paper is Li Z., Lee K., Karagas M. R., Madan J. C., Hoen A. G., O'Malley A. J. and Li H. (2018). "Conditional regression based on a multivariate zero-inflated logistic-normal model for microbiome relative abundance data", .

[cran] diffwrap 0.6-3

vidal.fey@gmail.com (Vidal Fey) — Sun, 30 Aug 2026 13:00:50 GMT

Functions for differential expression analysis of read counts from messenger RNA (mRNA) sequencing (RNA-Seq) data or micro RNA (miRNA) expression values generated by the Comprehensive Analysis Pipeline for microRNA Sequencing (CAP-miRSeq) 'expression_reports.sh' script. The workflow follows the 'edgeR'-'limma' expression data analysis pipeline providing options for different approaches, such as "pure" 'edgeR', voom or paired samples. The functions in the package generate text files with differential expression lists, optionally annotated with information from 'biomart', expression summary plots as well as several quality control (QC) plots. The main function, diffExpr(), is a convenience wrapper performing all steps automatically based on sensible defaults. Methods are described in Robinson, McCarthy and Smyth (2010) , Ritchie et al. (2015) , Law et al. (2014) and Sun et al. (2014) .

[cran] sstn 1.0.2

akin.anarat@hhu.de (Akin Anarat) — Sat, 29 Aug 2026 17:10:03 GMT

Implements the Self-Similarity Test for Normality (SSTN), a new statistical test designed to assess whether a given sample originates from a normal distribution. The method exploits the self-similarity property of the normal characteristic function by iteratively transforming and comparing standardized empirical characteristic functions. The null distribution of the test statistic is obtained via Monte Carlo simulation. Details of the methodology are described in Anarat and Schwender (2026), "A test for normality based on self-similarity", .

[cran] quickSentiment 0.3.6

alabhya.dahal@gmail.com (Alabhya Dahal) — Sat, 29 Aug 2026 02:19:45 GMT

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

[cran] extrafrail 1.15

dgallardo@ubiobio.cl (Diego Gallardo) — Sat, 29 Aug 2026 02:19:19 GMT

Provide estimation and data generation tools for new multivariate frailty models. This version includes the gamma, inverse Gaussian, weighted Lindley, Birnbaum-Saunders, truncated normal, mixture of inverse Gaussian, mixture of Birnbaum-Saunders, generalized exponential, Jorgensen-Seshadri-Whitmore, weighted Akash, weighted Shanker and weighted Sujatha as the distribution for frailty terms. For the basal model, it is considered a parametric approach based on the exponential, Weibull and the piecewise exponential distributions as well as a semiparametric approach. For details, see Gallardo et al. (2024) , Gallardo et al. (2025) , Kiprotich et al. (2025) , Gallardo et al. (2025) , Kiprotich et al. (2026)

[cran] LogicForest 2.1.5

melica.nikahd@osumc.edu (Melica Nikahd) — Sat, 29 Aug 2026 02:18:40 GMT

Logic Forest is an ensemble machine learning method that identifies important and interpretable combinations of binary predictors using logic regression trees to model complex relationships with an outcome. Wolf, B.J., Slate, E.H., Hill, E.G. (2010) .

[cran] npmv 2.5.0

wanda.lauth@pmu.ac.at (Wanda Lauth) — Fri, 28 Aug 2026 18:55:10 GMT

Performs analysis of one-way multivariate data, for small samples using Nonparametric techniques. Using approximations for ANOVA Type, Wilks' Lambda, Lawley Hotelling, and Bartlett Nanda Pillai Test statics, the package compares the multivariate distributions for a single explanatory variable. The comparison is also performed using a permutation test for each of the four test statistics. The package also performs an all-subsets algorithm regarding variables and regarding factor levels.

[cran] lnmCluster 1.0.0

wangshu.tu@carleton.ca (Wangshu Tu) — Fri, 28 Aug 2026 18:54:38 GMT

An implementation of logistic normal multinomial (LNM) clustering. It is an extension of LNM mixture model proposed by Fang and Subedi (2020) , and is designed for clustering compositional data. The package includes 3 extended models: LNM Factor Analyzer (LNM-FA), LNM Bicluster Mixture Model (LNM-BMM) and Penalized LNM Factor Analyzer (LNM-FA). There are several advantages of LNM models: 1. LNM provides more flexible covariance structure; 2. Factor analyzer can reduce the number of parameters to estimate; 3. Bicluster can simultaneously cluster subjects and taxa, and provides significant biological insights; 4. Penalty term allows sparse estimation in the covariance matrix. Details for model assumptions and interpretation can be found in papers: Tu and Subedi (2023) and Tu and Subedi (2022) . It also include a Biclustering algorithm that applies to multivariate normal data: Tu and Subedi (2022) .

[cran] layeranalyzer 0.4.1

trond.reitan@geo.uio.no (Trond Reitan) — Fri, 28 Aug 2026 18:54:33 GMT

Time series analysis tool using linear layered stochastic differential equations. The package allows for multiple time series with correlative and/or causal links between them. Unmeasured causal processes are allowed to affect the measured processes in a layered structure, hence the name of the package. In case of causal feedback loops, the matrix operations (including eigenvalue decompositions) allows for complex numbers. In this case, cyclic behavior can be expected. Details can be found in Reitan and Liow (2019).