New empirical Bayes methods aiming at analyzing the association of single nucleotide polymorphisms (SNPs) to some particular disease are implemented in this package. The package uses local false discovery rate (LFDR) estimates of SNPs within a sample population defined as a "reference class" and discovers if SNPs are associated with the corresponding disease. Although SNPs are used throughout this document, other biological data such as protein data and other gene data can be used. Karimnezhad, Ali and Bickel, D. R. (2016) <http://hdl.handle.net/10393/34889>.

This package implements a Gibbs sampler to do linear regression with multiple covariates, multiple responses, Gaussian measurement errors on covariates and responses, Gaussian intrinsic scatter, and a covariate prior distribution which is given by either a Gaussian mixture of specified size or a Dirichlet process with a Gaussian base distribution. Described further in Mantz (2016) <DOI:10.1093/mnras/stv3008>.

This package provides access to the LDlink API (<https://ldlink.nih.gov/?tab=apiaccess>) using the R console. This programmatic access facilitates researchers who are interested in performing batch queries in 1000 Genomes Project (2015) <doi:10.1038/nature15393> data using LDlink'. LDlink is an interactive and powerful suite of web-based tools for querying germline variants in human population groups of interest. For more details, please see Machiela et al. (2015) <doi:10.1093/bioinformatics/btv402>.

This package provides a graph proposed by Rosenbaum is useful for checking some properties of various sorts of latent scale, this program generates commands to obtain the graph using dot from graphviz'.

Extracts zip files, converts Word', Excel', and html'/'htm files to pdf format. Word and Excel conversion uses VBScript', while html'/'htm conversion uses webshot and PhantomJS'. Additionally, the package merges pdf files into a single document. This package is only supported on Windows due to VBScript dependencies.

Calculate point estimates of and valid confidence intervals for longitudinal summaries of nonparametric, algorithm-agnostic variable importance measures. For more details, see Williamson et al. (2024) <doi:10.48550/arXiv.2311.01638>.

This package provides a collection of lightweight, minimalist output formats and templates for litedown by Xie (2026) <doi:10.32614/CRAN.package.litedown>, including resumes, cover letters, and other common document types. Documents are rendered with HTML and CSS and can be printed to PDF with a Chromium'-based browser, without requiring Pandoc or a LaTeX installation.

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)<doi:10.1111/2041-210X.13299>.

This package provides a family of three complementary goodness-of-fit tests based on an adaptation of Hotelling's T-squared statistic applied to vectors of sample log-cumulants (Mellin statistics) for positive-support reliability data. The package provides the asymptotic chi-squared reference and parametric bootstrap p-values for reliable finite-sample inference, covering the Weibull, Frechet, Gamma, Inverse-Gamma, Log-Normal, and Log-Logistic families. It also provides three diagnostic diagrams (log-cumulant, kurtosis-skewness, and coefficient-of-variation) with bootstrap concentration ellipses, in the spirit of moment-ratio diagrams. Methods are described in Santos, Ospina, Espinheira and Oliveira (2025).

This package provides simple, reproducible access to datasets from the Los Angeles Open Data portal <https://data.lacity.org/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API.

Nonparametric methods for landmark prediction of long-term survival outcomes, incorporating covariate and short-term event information. The package supports the construction of flexible varying-coefficient models that use discrete covariates, as well as multiple continuous covariates. The goal is to improve prediction accuracy when censored short-term events are available as predictors, using robust nonparametric procedures that do not require correct model specification and avoid restrictive parametric assumptions found in alternative methods. More information on these methods can be found in Parast et al. 2012 <doi:10.1080/01621459.2012.721281>, Parast et al. 2011 <doi:10.1002/bimj.201000150>, and Parast and Cai 2013 <doi:10.1002/sim.5776>. A tutorial for this package is available here: <https://www.laylaparast.com/landpred>.

Read, register and compare point sets from single molecule localization microscopy.

This package creates shareable links for R code in WebAssembly (WASM) Read-Eval-Print Loop (REPL) environments like webR <https://webr.r-wasm.org/> and for Shiny applications using Shinylive <https://shinylive.io/>. Supports single scripts, multi-file projects, exercise and solution pairs, and batch processing. Includes encoding, decoding, and previewing of links for both R and Python environments.

When the values of the outcome variable Y are either 0 or 1, the function lsm() calculates the estimation of the log likelihood in the saturated model. This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3 through the assumptions 1 and 2. The function LogLik() works (almost perfectly) when the number of independent variables K is high, but for small K it calculates wrong values in some cases. For this reason, when Y is dichotomous and the data are grouped in J populations, it is recommended to use the function lsm() because it works very well for all K.

This package contains (1) event-related brain potential data recorded from 10 participants at electrodes Fz, Cz, Pz, and Oz (0--300 ms) in the context of Antoine Tremblay's PhD thesis (Tremblay, 2009); (2) ERP amplitudes at electrode Fz restricted to the 100 to 175 millisecond time window; and (3) plotting data generated from a linear mixed-effects model.

Package shiny provides interactive web applications in R. Package loon is an interactive toolkit engaged in open-ended, creative and unscripted data exploration. The loon.shiny package can take loon widgets and display a selfsame shiny app.

Routines to perform large scale regression. Linear, logistic, and Poisson regressions are supported. Large scale regression efficiently fits models where a small number of covariates are changing and the subjects have complete data. A genome wide association study would be an example.

Alternate font rendering is useful when rendering text to novel graphics outputs where modern font rendering is not available or where bespoke text positioning is required. Bitmap and vector fonts allow for custom layout and rendering using pixel coordinates and line drawing. Formatted text is created as a data.frame of pixel coordinates (for bitmap fonts) or stroke coordinates (for vector fonts). All text can be easily previewed as a matrix or raster image. A selection of fonts is included with this package.

This package provides R with the Glottolog database <https://glottolog.org/> and some more abilities for purposes of linguistic mapping. The Glottolog database contains the catalogue of languages of the world. This package helps researchers to make a linguistic maps, using philosophy of the Cross-Linguistic Linked Data project <https://clld.org/>, which allows for while at the same time facilitating uniform access to the data across publications. A tutorial for this package is available on GitHub pages <https://docs.ropensci.org/lingtypology/> and package vignette. Maps created by this package can be used both for the investigation and linguistic teaching. In addition, package provides an ability to download data from typological databases such as WALS, AUTOTYP and some others and to create your own database website.

An easy tool to transform 2D longitudinal data into 3D arrays suitable for Long short-term memory neural networks training. The array output can be used by the keras package. Long short-term memory neural networks are described in: Hochreiter, S., & Schmidhuber, J. (1997) <doi:10.1162/neco.1997.9.8.1735>.

This package provides missing data imputation through two complementary engines: a large language model engine that communicates with the Anthropic Claude application programming interface for context-aware semantic imputation, and a fully self-contained offline engine implementing nineteen statistical and machine learning algorithms entirely in base R with no additional package dependencies. Offline methods include mean, median, mode, last observation carried forward, next observation carried backward, hot-deck, predictive mean matching, k-nearest neighbours, ordinary least-squares regression, Lasso with coordinate descent, Ridge with closed-form solution, Bayesian Ridge regression with evidence approximation following MacKay (1992), support vector regression with a radial basis function kernel, classification and regression trees, random forests, gradient boosting, iterative random forest imputation, principal component analysis imputation via iterative singular value decomposition, and nuclear-norm minimisation via singular value thresholding. When no API key is available the package automatically falls back to the offline engine, ensuring full operation in environments without internet access. Every imputed value is accompanied by a confidence score and a plain-language reasoning string, producing reproducible audit trails. The automatic method selector chooses the best algorithm per column based on data type, skewness, missingness rate, and inter-column correlations.

This package performs the trimmed k-means clustering algorithm with lower memory use. It also provides a number of utility functions such as BIC calculations.

This package provides a framework to load text and excel files through a shiny graphical interface. It allows renaming, transforming, ordering and removing variables. It includes basic exploratory methods such as the mean, median, mode, normality test, histogram and correlation.

Maximum likelihood estimation and likelihood ratio test are essential for modern statistics. This package supports in calculating likelihood based inference. Reference: Pawitan Y. (2001, ISBN:0-19-850765-8).