Distributes data from the Polarization in Comparative Attitudes Project. Helper functions enable data retrieval in wide and tidy formats for user-defined countries and years. Provides support for case-insensitive country names in many languages. Mehlhaff (2022) <https://imehlhaff.net/files/Polarization%20and%20Democracy.pdf>.

Explore the world of R graphics with fun and interesting plot functions! Use make_LED() to create dynamic LED screens, draw interconnected rings with Olympic_rings(), and make festive Chinese couplets with chunlian(). Unleash your creativity and turn data into exciting visuals!

This package provides robust functions for proportional allocation of numeric values. It guarantees sum consistency after rounding or integer truncation using one of two adjustment methods: the largest remainder method or max-value adjustment. Handles edge cases like NA weights and vector total values seamlessly.

The function syncSubsample subsamples temporal data of different entities so that the result only contains synchronal events. The function mci calculates the Movement Coordination Index (MCI, see reference on help page for function mci') of a data set created with the function syncSubsample'.

S-Core Graph Decomposition algorithm for graphs. This is a method for decomposition of a weighted graph, as proposed by Eidsaa and Almaas (2013) <doi:10.1103/PhysRevE.88.062819>. The high speed and the low memory usage make it suitable for large graphs.

This package implements automatic autoregressive integrated moving average order selection using the Spider Monkey Optimization algorithm. Candidate orders are evaluated using a weighted objective function that combines the Akaike information criterion and root mean square error. Functions support model fitting, forecasting, and forecast accuracy evaluation.

Simple class to hold contents of a SMET file as specified in Bavay (2021) <https://code.wsl.ch/snow-models/meteoio/-/blob/master/doc/SMET_specifications.pdf>. There numerical meteorological measurements are all based on MKS (SI) units and timestamp is standardized to UTC time.

This package provides a convenient way to log scalars, images, audio, and histograms in the tfevent record file format. Logged data can be visualized on the fly using TensorBoard', a web based tool that focuses on visualizing the training progress of machine learning models.

This package provides a suite of functions for analysing, interpreting, and visualising time-series features calculated from different feature sets from the theft package. Implements statistical learning methodologies described in Henderson, T., Bryant, A., and Fulcher, B. (2023) <doi:10.48550/arXiv.2303.17809>.

This package provides a convenient wrapper for the UM-Bridge protocol. UM-Bridge is a protocol designed for coupling uncertainty quantification (or statistical / optimization) software to numerical models. A model is represented as a mathematical function with optional support for derivatives via Jacobian actions etc.

R is used by a vast array of people for a vast array of purposes - including web analytics. This package contains functions for consuming and munging various common forms of request log, including the Common and Combined Web Log formats and various Amazon access logs.

cl-ratify is a collection of utilities to perform validation checks and parsing. The main intention of usage for this is in web-applications in order to check form inputs for correctness and automatically parse them into their proper representations or return meaningful errors.

Deterministic, name-blind detection of variable roles (group, outcome, survival time and event, paired and agreement measurements, repeated measures, scale items, subject identifier, covariate) in tabular data. Roles are assigned from each column's information-theoretic signature -- Shannon entropy, normalized mutual information, and distributional shape -- rather than from column names, so renaming columns to col_1', col_2', ... does not change the result ("Data inspice, non nomen"). An optional, capped name-based hint and automatic header-row detection are also provided. No large language models and no external data transmission. Extracted from the MDStatR biostatistics engine; see Boynukara (2026) <doi:10.5281/zenodo.20707791>.

This package implements the empirical test introduced by Yu, Ge, and Elwert (2026) for detecting when randomized interventional analogues should not be interpreted as natural mediation effects. The package estimates natural effects, their randomized interventional analogues, and TE - TE^R, the difference between the total effect and its randomized interventional analogue. Rejecting TE - TE^R = 0 falsifies the composite null that the natural indirect and direct effects equal their randomized interventional analogues. The procedure remains valid in settings where the natural effects themselves are not identified, and |TE - TE^R| provides a lower bound on the total divergence between the natural and randomized interventional decompositions.

Aims at loading Google Adwords data into R. Adwords is an online advertising service that enables advertisers to display advertising copy to web users (see <https://developers.google.com/adwords/> for more information). Therefore the package implements three main features. First, the package provides an authentication process for R with the Google Adwords API (see <https://developers.google.com/adwords/api/> for more information) via OAUTH2. Second, the package offers an interface to apply the Adwords query language in R and query the Adwords API with ad-hoc reports. Third, the received data are transformed into suitable data formats for further data processing and data analysis.

Ritornello is a ChIP-seq peak calling algorithm based on signal processing that can accurately call binding events without the need to do a pair total DNA input or IgG control sample. It has been tested for use with narrow binding events such as transcription factor ChIP-seq.

This package performs projection predictive feature selection for generalized linear models and generalized linear and additive multilevel models. The package is compatible with the rstanarm and brms packages, but other reference models can also be used. See the package vignette for more information and examples.

This package constructs basis functions of B-splines, M-splines, I-splines, convex splines (C-splines), periodic splines, natural cubic splines, generalized Bernstein polynomials, their derivatives, and integrals (except C-splines) by closed-form recursive formulas. It also contains a C++ head-only library integrated with Rcpp.

This package provides an estimation and inference methods for models of conditional quantiles: linear and nonlinear parametric and non-parametric models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.

Comprehensive and flexible logging library written in Ruby for use in Ruby programs. It features a hierarchical logging system of any number of levels, custom level names, logger inheritance, multiple output destinations per log event, execution tracing, custom formatting, thread safteyness, XML and YAML configuration, and more.

Subtypes are defined as groups of samples that have distinct molecular and clinical features. Genomic data can be analyzed for discovering patient subtypes, associated with clinical data, especially for survival information. This package is aimed to identify subtypes that are both clinically relevant and biologically meaningful.

Splatter is a package for the simulation of single-cell RNA sequencing count data. It provides a simple interface for creating complex simulations that are reproducible and well-documented. Parameters can be estimated from real data and functions are provided for comparing real and simulated datasets.

Colour palettes and a ggplot2 theme to follow the UK Government Analysis Function best practice guidance for producing data visualisations, available at <https://analysisfunction.civilservice.gov.uk/policy-store/data-visualisation-charts/>. Includes continuous and discrete colour and fill scales, as well as a ggplot2 theme.

This package implements Bayesian marginal structural models for causal effect estimation with time-varying treatment and confounding. It includes an extension to handle informative right censoring. The Bayesian importance sampling weights are estimated using JAGS. See Saarela (2015) <doi:10.1111/biom.12269> for methodological details.