This package contains functions for a two-stage multiple testing procedure for grouped hypothesis, aiming at controlling both the total posterior false discovery rate and within-group false discovery rate.

Computation of generalized hypergeometric function with tunable high precision in a vectorized manner, with the floating-point datatypes from mpfr or gmp library. The computation is limited to real numbers.

Merges and downloads SPSS data from different International Large-Scale Assessments (ILSA), including: Trends in International Mathematics and Science Study (TIMSS), Progress in International Reading Literacy Study (PIRLS), and others.

Draw 2 dimensional and three dimensional plot for multiple regression models using package ggplot2 and rgl'. Supports linear models (lm), generalized linear models (glm) and local polynomial regression fittings (loess).

Model Selection Based on Combined Penalties. This package implements a stepwise forward variable selection algorithm based on a penalized likelihood criterion that combines the L0 with L2 or L1 norms.

Tree-structured modelling of categorical predictors (Tutz and Berger (2018), <doi:10.1007/s11634-017-0298-6>) or measurement units (Berger and Tutz (2018), <doi:10.1080/10618600.2017.1371030>).

This package creates interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. treeheatr utilizes the customizable ggparty package for drawing decision trees.

Download and compile any version of the IANA Time Zone Database (also known as Olson database) and make it current in your R session. Beware: on Windows Cygwin is required!

Random-intercept accelerated failure time (AFT) model utilizing Bayesian additive regression trees (BART) for drawing causal inferences about multiple treatments while accounting for the multilevel survival data structure. It also includes an interpretable sensitivity analysis approach to evaluate how the drawn causal conclusions might be altered in response to the potential magnitude of departure from the no unmeasured confounding assumption.This package implements the methods described by Hu et al. (2022) <doi:10.1002/sim.9548>.

Set of tools for reading and processing spatial data. The aim is to supply the workflow to create thematic maps. This package also facilitates tmap, the package for visualizing thematic maps.

This package provides color palettes. They are checked for colorblind accessibility from hue, saturation, and lightness value scaling using the Chroma.js Color Palette Helper. See https://gka.github.io/palettes.

Qucsator-rf is a command line driven circuit simulator targeted for RF and microwave circuits. It takes a network list in a certain format as input and outputs an XML dataset.

This package provides a fake file system for use in test suites. It avoids the need for manually creating temporary directories, or dealing with platform intricacies in File and FileUtils.

Merging of mixture components for model-based automated gating of flow cytometry data using the flowClust framework. Note: users should have a working copy of flowClust 2.0 installed.

This package extends flowCore to provide functionality specific to bead data. One of the goals of this package is to automate analysis of bead data for the purpose of normalisation.

Extracted features from pathways derived from 8 different databases (KEGG, Reactome, Biocarta, etc.) can be used on transcriptomic, proteomic, and/or metabolomic level to calculate a combined GSEA-based enrichment score.

Extends package arules with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration. Michael Hahsler (2017) <doi:10.32614/RJ-2017-047>.

This package provides a set of functions for interacting with the DigitalOcean API <https://www.digitalocean.com/>, including creating images, destroying them, rebooting, getting details on regions, and available images.

Facilitates local polynomial regression for state dependent covariates in state-space models. The functionality can also be used from C++ based model builder tools such as Rcpp'/'inline', TMB', or JAGS'.

Compressed spatial vector data originally from <https://dawadocs.dataforsyningen.dk/> saved as Simple Features, SF, objects with data on population, age and gender from Statistics Denmark <https://www.dst.dk/da/>.

This package provides tools for describing and analysing free sorting data. Main methods are computation of consensus partition and factorial analysis of the dissimilarity matrix between stimuli (using multidimensional scaling approach).

This package provides functions for selecting attributes from a given dataset. Attribute subset selection is the process of identifying and removing as much of the irrelevant and redundant information as possible.

Flipbooks present code step-by-step and side-by-side with its output. flipbookr helps creators build flipbooks efficiently because code pipelines are automatically parsed and prepped for presentation as flipbooks.

Reconstruction of muscle fibers from image stacks using textural analysis. Includes functions for tracking, smoothing, cleaning, plotting and exporting muscle fibers. Also calculates basic fiber properties (e.g., length and curvature).