This package provides the infrastructure to define and analyze the solutions of Partially Observable Markov Decision Process (POMDP) models. Interfaces for various exact and approximate solution algorithms are available including value iteration, point-based value iteration and SARSOP. Hahsler and Cassandra <doi:10.32614/RJ-2024-021>.

This package provides a collection of statistical hypothesis tests of functional time series. While it will include more tests when the related literature are enriched, this package contains the following key tests: functional stationarity test, functional trend stationarity test, functional unit root test, to name a few.

Compute relative or absolute population trends across space and time using predictions from models fitted to ecological population abundance data, as described in Knape (2025) <doi:10.1016/j.ecolind.2025.113435>. The package supports models fitted by mgcv or brms', and draws from posterior predictive distributions.

SMAHP (pronounced as SOO-MAP) is a novel multi-omics framework for causal mediation analysis of high-dimensional proteogenomic data with survival outcomes. The full methodological details can be found in our recent preprint by Ahn S et al. (2025) <doi:10.48550/arXiv.2503.08606>.

This package provides tools for estimating and inferring two-way partial area under receiver operating characteristic curves (two-way pAUC), partial area under receiver operating characteristic curves (pAUC), and partial area under ordinal dominance curves (pODC). Methods includes Mann-Whitney statistic and Jackknife, etc.

This package provides an R interface to the Whapi API <https://whapi.cloud>, enabling sending and receiving WhatsApp messages directly from R'. Functions include sending text, images, documents, stickers, geographic locations, and interactive messages (buttons and lists). Also includes webhook parsing utilities and channel health checks.

Computation of the International Roughness Index (IRI) given a longitudinal road profile. The IRI can be calculated for a single road segment or for a sequence of segments with a fixed length (e. g. 100m). For the latter, an overlap of the segments can be selected. The IRI and likewise the algorithms for its determination are defined in Sayers, Michael W; Gillespie, Thomas D; Queiroz, Cesar A.V. 1986. The International Road Roughness Experiment (IRRE) : establishing correlation and a calibration standard for measurements. World Bank technical paper; no. WTP 45. Washington, DC : The World Bank. (ISBN 0-8213-0589-1) available from <http://documents.worldbank.org/curated/en/326081468740204115>.

This package lets you create extra Analysis Results Data (ARD) summary objects. The package supplements the simple ARD functions from the cards package, exporting functions to put statistical results in the ARD format. These objects are used and re-used to construct summary tables, visualizations, and written reports.

This package provides a header only, C++11 interface to R's C interface. Compared to other approaches cpp11 strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with ALTREP vectors.

This package lets you construct Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Results Data objects. These objects are used and re-used to construct summary tables, visualizations, and written reports. The package also exports utilities for working with these objects and creating new Analysis Results Data objects.

Users may want to align plots with associated information that requires axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. This package provides utilities to align associated subplots to a main plot at different sides (left, right, top and bottom) with axes exactly matched.

Rsyslog offers high-performance, great security features and a modular design. While it started as a regular syslogd, rsyslog has evolved into a kind of swiss army knife of logging, being able to accept inputs from a wide variety of sources, transform them, and output the results to diverse destinations.

This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).

This package provides a tool to measure reproducibility between genomic experiments that produce two-dimensional peaks (interactions between peaks), such as ChIA-PET, HiChIP, and HiC. idr2d is an extension of the original idr package, which is intended for (one-dimensional) ChIP-seq peaks.

PhosR is a package for the comprenhensive analysis of phosphoproteomic data. There are two major components to PhosR: processing and downstream analysis. PhosR consists of various processing tools for phosphoproteomics data including filtering, imputation, normalisation, and functional analysis for inferring active kinases and signalling pathways.

The qsvaR package contains functions for removing the effect of degration in rna-seq data from postmortem brain tissue. The package is equipped to help users generate principal components associated with degradation. The components can be used in differential expression analysis to remove the effects of degradation.

Comprehensive Business Process Analysis toolkit. Creates S3-class for event log objects, and related handler functions. Imports related packages for filtering event data, computation of descriptive statistics, handling of Petri Net objects and visualization of process maps. See also packages edeaR','processmapR', eventdataR and processmonitR'.

This package provides a wrapper to allow users to download Bus Open Data Service BODS transport information from the API (<https://www.bus-data.dft.gov.uk/>). This includes timetable and fare metadata (including links for full datasets), timetable data at line level, and real-time location data.

Gaussian mixture modeling of one- and two-dimensional data, provided in original or binned form, with an option to estimate the number of model components. The method uses Gaussian Mixture Models (GMM) with initial parameters determined by a dynamic programming algorithm, leading to stable and reproducible model fitting.

Descarga, lee y analiza bases de la Encuesta Nacional de Hogares (ENAHO) y otras encuestas del Instituto Nacional de Estadà stica e Informática (INEI) del Perú. (Downloads, reads, and combines data from the Peruvian Home National Survey and other surveys from the National Institute for Statistics (INEI).).

The purpose of this package is to generate trees and validate unverified code. Trees are made by parsing a statement into a verification tree data structure. This will make it easy to port the statement into another language. Safe statement evaluations are done by executing the verification trees.

Datasets for teaching quantitative approaches and modeling in archaeology and paleontology. This package provides several types of data related to broad topics (cultural evolution, radiocarbon dating, paleoenvironments, etc.), which can be used to illustrate statistical methods in the classroom (multivariate data analysis, compositional data analysis, diversity measurement, etc.).

Efficient implementations of the algorithms in the Almost-Matching-Exactly framework for interpretable matching in causal inference. These algorithms match units via a learned, weighted Hamming distance that determines which covariates are more important to match on. For more information and examples, see the Almost-Matching-Exactly website.

This General Regression Neural Networks Package uses various distance functions. It was motivated by Specht (1991, ISBN:1045-9227), and updated from previous published paper Li et al. (2016) <doi:10.1016/j.palaeo.2015.11.005>. This package includes various functions, although "euclidean" distance is used traditionally.