Fast randomization based two sample tests. Testing the hypothesis that two samples come from the same distribution using randomization to create p-values. Included tests are: Kolmogorov-Smirnov, Kuiper, Cramer-von Mises, Anderson-Darling, Wasserstein, and DTS. The default test (two_sample) is based on the DTS test statistic, as it is the most powerful, and thus most useful to most users. The DTS test statistic builds on the Wasserstein distance by using a weighting scheme like that of Anderson-Darling. See the companion paper at <arXiv:2007.01360> or <https://codowd.com/public/DTS.pdf> for details of that test statistic, and non-standard uses of the package (parallel for big N, weighted observations, one sample tests, etc). We also include the permutation scheme to make test building simple for others.

Enables the acquisition of Korean financial market data, designed to integrate seamlessly with the tidyquant package.

This package implements two-mode clustering (biclustering) using genetic algorithms. The method was first introduced in Hageman et al. (2008) <doi:10.1007/s11306-008-0105-7>. The package provides tools for fitting, visualization, and validation of two-mode cluster structures in data matrices.

Compute arbitrary non-parametric bootstrap statistics on data in tidy data frames.

An R interface to the Open Data API of the Tribunal de Contas do Estado de Pernambuco (TCE-PE), the Court of Accounts of the State of Pernambuco, Brazil. Provides tidy, ready-to-use functions to query public data on revenues, expenditures, commitments, procurement, contracts, agreements, public works, legal processes, personnel and reference tables for all state and municipal government entities in Pernambuco. All results are returned as tibbles with column names converted to snake_case by default. Uses httr2 for HTTP requests and cli for user-friendly messages. See <https://sistemas.tcepe.tc.br/DadosAbertos/> for the API documentation.

Provide data generation and estimation tools for the truncated positive normal (tpn) model discussed in Gomez, Olmos, Varela and Bolfarine (2018) <doi:10.1007/s11766-018-3354-x>, the slash tpn distribution discussed in Gomez, Gallardo and Santoro (2021) <doi:10.3390/sym13112164>, the bimodal tpn distribution discussed in Gomez et al. (2022) <doi:10.3390/sym14040665>, the flexible tpn model <doi:10.3390/math11214431> and the unit tpn distribution <doi:10.1016/j.chemolab.2025.105322>.

Test the nullity of covariances, in a set of variables, using a simple univariate procedure. See Marques, Diago, Norouzirad, Bispo (2023) <doi:10.1002/mma.9130>.

This package provides various commonly-used response time trimming methods, including the recursive / moving-criterion methods reported by Van Selst and Jolicoeur (1994). By passing trimming functions raw data files, the package will return trimmed data ready for inferential testing.

Density, distribution function, the quantile function, random generation function, and maximum likelihood estimation.

Simulates typing of R script files for presentations and demonstrations. Provides character-by-character animation with optional live code execution. Supports R scripts (.R), R Markdown (.Rmd), and Quarto (.qmd) documents.

This package provides tools to help developers and producers manipulate R objects and outputs. It includes tools for displaying results and objects, and for formatting them in the correct format.

Agglomerative hierarchical clustering with a bespoke distance measure based on medication similarities in the Anatomical Therapeutic Chemical Classification System, medication timing and medication amount or dosage. Tools for summarizing, illustrating and manipulating the cluster objects are also available.

Find the optimal decision rules (AKA progression criteria) and sample size for clinical trials with three (stop/pause/go) outcomes. Both binary and continuous endpoints can be accommodated, as can cases where an adjustment is planned following a pause outcome. For more details see Wilson et al. (2024) <doi:10.1186/s12874-024-02351-x>.

This package provides a Tcl/Tk Graphical User Interface (GUI) to display images than can be zoomed and panned using the mouse and keyboard shortcuts. tkImgR read and write different image formats (PPM/PGM, PNG and GIF) using the standard Tcl/Tk distribution (>=8.6), but other formats (JPEG, TIFF, CR2) can be handled using the tkImg package for Tcl/Tk'.

This package implements simulated tests for the hypothesis that terminal digits are uniformly distributed (chi-squared goodness-of-fit) and the hypothesis that terminal digits are independent from preceding digits (several tests of independence for r x c contingency tables). Also, for a number of distributions, implements Monte Carlo simulations for type I errors and power for the test of independence.

The satisfaction Analysis using the tetraclasse model from Sylvie Llosa. Llosa (1997) <http://www.jstor.org/stable/40592578>.

Enables all rstan functionality for a TMB model object, in particular MCMC sampling and chain visualization. Sampling can be performed with or without Laplace approximation for the random effects. This is demonstrated in Monnahan & Kristensen (2018) <DOI:10.1371/journal.pone.0197954>.

This is a simple addin to RStudio that finds all TODO', FIX ME', CHANGED etc. comments in your project and shows them as a markers list.

This package provides a dataset of predefined color palettes based on the Star Trek science fiction series, associated color palette functions, and additional functions for generating customized palettes that are on theme. The package also offers functions for applying the palettes to plots made using the ggplot2 package.

Longitudinal data offers insights into population changes over time but often requires a flexible structure, especially with varying follow-up intervals. Panel data is one way to store such records, though it adds complexity to analysis. The tvtools package for R simplifies exploring and analyzing panel data.

The goal of tor (to-R) is to help you to import multiple files from a single directory at once, and to do so as quickly, flexibly, and simply as possible.

Package test2norm contains functions to generate formulas for normative standards applied to cognitive tests. It takes raw test scores (e.g., number of correct responses) and converts them to scaled scores and demographically adjusted scores, using methods described in Heaton et al. (2003) <doi:10.1016/B978-012703570-3/50010-9> & Heaton et al. (2009, ISBN:9780199702800). The scaled scores are calculated as quantiles of the raw test scores, scaled to have the mean of 10 and standard deviation of 3, such that higher values always correspond to better performance on the test. The demographically adjusted scores are calculated from the residuals of a model that regresses scaled scores on demographic predictors (e.g., age). The norming procedure makes use of the mfp2() function from the mfp2 package to explore nonlinear associations between cognition and demographic variables.

Compute and visualize the Tissot Indicatrix for map projections. The indicatrix characterizes projection distortion by computing scale factors, angular deformation, areal distortion, and convergence at arbitrary points. Based on the calculations shared by Bill Huber on <https://gis.stackexchange.com/a/5075/482>. Uses GDAL for coordinate transformation. Developed using the method published in Snyder, JP (1987) <doi:10.3133/pp1395>.

This package contains some auxiliary functions.