Generate multiple data sets for educational purposes to demonstrate the importance of multiple regression. The genset function generates a data set from an initial data set to have the same summary statistics (mean, median, and standard deviation) but opposing regression results.

Implementations of the treatment effect estimators for hybrid (self-selection) experiments, as developed by Brian J. Gaines and James H. Kuklinski, (2011), "Experimental Estimation of Heterogeneous Treatment Effects Related to Self-Selection," American Journal of Political Science 55(3): 724-736.

This package provides a tool to sensitivity analysis using SOBOL (Sobol, 1993) and AMA (Dell'Oca et al. 2017 <doi:10.5194/hess-21-6219-2017>) indices. It allows to identify the most sensitive parameter or parameters of a model.

Graceful ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the mgcv package. Provides a reimplementation of the plot() method for GAMs that mgcv provides, as well as tidyverse compatible representations of estimated smooths.

This package contains published data sets for global benthic d18O data for 0-5.3 Myr <doi:10.1029/2004PA001071> and global sea levels based on marine sediment core data for 0-800 ka <doi:10.5194/cp-12-1-2016>.

Estimate parameters of the hysteretic threshold autoregressive (HysTAR) model, using conditional least squares. In addition, you can generate time series data from the HysTAR model. For details, see Li, Guan, Li and Yu (2015) <doi:10.1093/biomet/asv017>.

Implementation of MCMC algorithms to estimate the Hierarchical Dirichlet Process Generalized Linear Model (hdpGLM) presented in the paper Ferrari (2020) Modeling Context-Dependent Latent Heterogeneity, Political Analysis <DOI:10.1017/pan.2019.13> and <doi:10.18637/jss.v107.i10>.

Converts among many citation formats, including BibTeX', Citeproc', Codemeta', RDF XML', RIS', Schema.org', and Citation File Format'. A low level R6 class is provided, as well as stand-alone functions for each citation format for both read and write.

This package provides functions to perform discriminant analysis using kernel density estimation. For the case of binary classification the package relies on the Nadaraya-Watson estimator. References: Wand M.P. and Jones M.C. (1995). "Kernel smoothing". CRC Press. <ISBN: 0412552701>.

Convert an R Markdown documents into an .xlsx spreadsheet reports with the knitxl() function, which works similarly to knit() from the knitr package. The generated report can be opened in Excel or similar software for further analysis and presentation.

This toolkit allows performing continuous-time microsimulation for a wide range of life science (demography, social sciences, epidemiology) applications. Individual life-courses are specified by a continuous-time multi-state model as described in Zinn (2014) <doi:10.34196/IJM.00105>.

Support the book: Wu CO and Tian X (2018). Nonparametric Models for Longitudinal Data. Chapman & Hall/CRC (to appear); and provide fit for using global and local smoothing methods for the conditional-mean and conditional-distribution based models with longitudinal Data.

Fits nuclear norm penalized multivariate linear regression models using the fast iterative shrinkage-thresholding algorithm (FISTA) of Beck and Teboulle (2009) <doi:10.1137/080716542>. Provides fixed-penalty estimation, regularization paths, K-fold cross-validation, prediction, coefficient extraction, and diagnostic plots.

Computes penalized regression calibration (PRC), a statistical method for the dynamic prediction of survival when many longitudinal predictors are available. See Signorelli (2024) <doi:10.32614/RJ-2024-014> and Signorelli et al. (2021) <doi:10.1002/sim.9178> for details.

This package provides functions to convert text data for labelling into format appropriate for importing into Qualtrics. Supports multiple language, including right-to-left scripts as well as different response types. Outputs an Advance Format .txt file that read into Qualtrics.

Simplifies output suppression logic in R packages, as it's common to develop some form of it in R. quietR intends to simplify that problem and allow a set of simple toggle functions to be used to suppress console output.

Identifies principal components whose eigenvalues exceed those expected under noise. Implements analytical thresholds derived from the Marchenko-Pastur distribution (Marchenko and Pastur, 1967) <doi:10.1070/SM1967v001n04ABEH001994> and empirical permutation tests, and provides functions for visualizing observed and null eigenvalue spectra.

It builds dynamic R shiny based dashboards to analyze any CSV files. It provides simple dashboard design to subset the data, perform exploratory data analysis and preliminary machine learning (supervised and unsupervised). It also provides filters based on columns of interest.

Routines for the seasonal analysis of health data, including regression models, time-stratified case-crossover, plotting functions and residual checks, see Barnett and Dobson (2010) ISBN 978-3-642-10748-1. Thanks to Yuming Guo for checking the case-crossover code.

Assess essential unidimensionality using external validity information using the procedure proposed by Ferrando & Lorenzo-Seva (2019) <doi:10.1177/0013164418824755>. Provides two indices for assessing differential and incremental validity, both based on a second-order modelling schema for the general factor.

This package provides functions for the creation and manipulation of scenes and objects within the Unity 3D video game engine (<https://unity.com/>). Specific focuses include the creation and import of terrain data and GameObjects as well as scene management.

This package provides a classifier independent filter method for high-dimensional gene-expression feature selection. The Run Purity Weighted Nearest Shrunken Centroid ('RPWNSC') score ranks genes by multiplying a run based purity score, which measures the compactness of class labels after sorting samples by each feature, by a scaled nearest shrunken centroid score, which measures standardized class centroid separation relative to within class variation. The top ranked features can then be used with downstream classifiers without wrapper search, feature clustering, or classifier dependent training. Amjad Ali, Zardad Khan, Saeed Aldahmani (2026) <doi:10.1016/j.mlwa.2026.100947>.

This package contains the resample and windowfilter command line utilities. The resample command allows changing the sampling rate of a sound file, while the windowfilter command allows designing Finite Impulse Response (FIR) filters using the so-called window method.

This package generates interactive visualisations for analysis of RNA-sequencing data using output from limma, edgeR or DESeq2 packages in an HTML page. The interactions are built on top of the popular static representations of analysis results in order to provide additional information.