This package implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices.

This package provides functions for viewing 2D and 3D data, including perspective plots, slice plots, surface plots, scatter plots, etc. It includes data sets from oceanography.

This package implements targeted minimum loss-based estimators of counterfactual means and causal effects that are doubly-robust with respect both to consistency and asymptotic normality.

This package provides density, distribution, quantile and hazard functions of a stable variate, as well as generalized regression models for the parameters of a stable distribution.

This package provides a convenience wrapper that uses the rmarkdown package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites or email. reprex also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.

Perform mediation analysis via the fast-and-robust bootstrap test ROBMED (Alfons, Ates & Groenen, 2022a; <doi:10.1177/1094428121999096>), as well as various other methods. Details on the implementation and code examples can be found in Alfons, Ates, and Groenen (2022b) <doi:10.18637/jss.v103.i13>. Further discussion on robust mediation analysis can be found in Alfons & Schley (2025) <doi:10.31234/osf.io/2hqdy>.

Simplifies aspects of linear regression analysis, particularly simultaneous inference. Additionally, supports "A Progressive Introduction to Linear Models" by Joshua French (<https://jfrench.github.io/LinearRegression/>).

This package provides methods for fitting identity-link GLMs and GAMs to discrete data, using EM-type algorithms with more stable convergence properties than standard methods.

Data on Asylum and Resettlement for the UK, provided by the Home Office <https://www.gov.uk/government/statistical-data-sets/immigration-system-statistics-data-tables>.

The BAGofT assesses the goodness-of-fit of binary classifiers. Details can be found in Zhang, Ding and Yang (2021) <arXiv:1911.03063v2>.

Helpful functions for the cleaning and manipulation of surveillance data, especially with regards to the creation and validation of panel data from individual level surveillance data.

Perform bulk and cell type-specific expression quantitative trail loci mapping with our novel method (Little et al. (2023) <doi:10.1038/s41467-023-38795-w>).

This package provides functions for evaluating and visualizing ecological assessment procedures for surface waters containing physical, chemical and biological assessments in the form of value functions.

Log-ratio Lasso regression for continuous, binary, and survival outcomes with (longitudinal) compositional features. See Fei and others (2024) <doi:10.1016/j.crmeth.2024.100899>.

This package provides functions for financial analysis and financial modeling, including batch graphs generation, beta calculation, descriptive statistics, annuity calculation, bond pricing and financial data download.

This package provides a Gaussian or Student's t copula-based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.

Assists in generating binary clustered data, estimates of Intracluster Correlation coefficient (ICC) for binary response in 16 different methods, and 5 different types of confidence intervals.

This package provides methods for fitting log-link GLMs and GAMs to binomial data, including EM-type algorithms with more stable convergence properties than standard methods.

Find dark genes. These genes are often disregarded due to no detected mutation or differential expression, but are important in coordinating the functionality in cancer networks.

This package provides methods of selecting one from many numeric predictors for a regression model, to ensure that the additional predictor has the maximum effect size.

This package provides functions are primarily functions for systems of ordinary differential equations, difference equations, and eigenanalysis and projection of demographic matrices; data are for examples.

Features unstructured, structured and reverse geocoding using the photon geocoding API <https://photon.komoot.io/>. Facilitates the setup of local photon instances to enable offline geocoding.

Compute various quantitative genetics parameters from a Generalised Linear Mixed Model (GLMM) estimates. Especially, it yields the observed phenotypic mean, phenotypic variance and additive genetic variance.

Develops a framework for fisheries stock assessment simulation testing with Stock Synthesis (SS) as described in Anderson et al. (2014) <doi:10.1371/journal.pone.0092725>.