Perform a Bayesian estimation of the exploratory deterministic input, noisy and gate (EDINA) cognitive diagnostic model described by Chen et al. (2018) <doi:10.1007/s11336-017-9579-4>.

Add a scroll back to top Font Awesome icon <https://fontawesome.com/> in rmarkdown documents and shiny apps thanks to jQuery GoTop <https://scottdorman.blog/jquery-gotop/>.

This package provides tools for multivariate nonparametrics, as location tests based on marginal ranks, spatial median and spatial signs computation, Hotelling's T-test, estimates of shape are implemented.

Mixture modelling of one-dimensional data using combinations of left-truncated Gamma, Weibull, and Lognormal Distributions. Blostein, Martin & Miljkovic, Tatjana. (2019) <doi:10.1016/j.insmatheco.2018.12.001>.

This package provides a suite of functions for reading in a rate file in XML format, stratify a cohort, and calculate SMRs from the stratified cohort and rate file.

This package provides the method for computing the local partial autocorrelation function for locally stationary wavelet time series from Killick, Knight, Nason, Eckley (2020) <doi:10.1214/20-EJS1748>.

This package provides a set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.

Use phenotype risk scores based on linked clinical and genetic data to study Mendelian disease and rare genetic variants. See Bastarache et al. 2018 <doi:10.1126/science.aal4043>.

Reads in multi-part parquet files. Will read in parquet files that have not been previously coalesced into one file. Convenient for reading in moderately sized, but split files.

Bayesian variable selection for regression models of under-reported count data as well as for (overdispersed) Poisson, negative binomal and binomial logit regression models using spike and slab priors.

This package provides access to material from the book "Processing and Analyzing Financial Data with R" by Marcelo Perlin (2017) available at <https://sites.google.com/view/pafdr/home>.

This package provides a method for the quantitative prediction with much predictors. This package provides functions to construct the quantitative prediction model with less overfitting and robust to noise.

Large-scale gene expression studies allow gene network construction to uncover associations among genes. This package is developed for estimating and testing partial correlation graphs with prior information incorporated.

This package provides a function to convert PRQL strings to SQL strings. Combined with other R functions that take SQL as an argument, PRQL can be used on R.

This package provides a graphical user interface for viewing and designing various types of graphs of the data. The graphs can be saved in different formats of an image.

Sometimes you need to split your data and work on the two chunks independently before bringing them back together. Taber allows you to do that with its two functions.

This package provides an overview of the demand for natural gas in the US by state and country level. Data source: US Energy Information Administration <https://www.eia.gov/>.

This package provides a hiredis wrapper that includes support for transactions, pipelining, blocking subscription, serialisation of all keys and values, Redis error handling with R errors. It includes an automatically generated R6 interface to the full hiredis API. Generated functions are faithful to the hiredis documentation while attempting to match R's argument semantics. Serialization must be explicitly done by the user, but both binary and text-mode serialisation is supported.

This package implements specialized algorithms that enable genetic ancestry inference from various cancer sequences sources (RNA, Exome and Whole-Genome sequences). This package also implements a simulation algorithm that generates synthetic cancer-derived data. This code and analysis pipeline was designed and developed for the following publication: Belleau, P et al. Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms. Cancer Res 1 January 2023; 83 (1): 49–58.

An approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for 210Pb-dated deposits using prior information. It can combine 210Pb, radiocarbon, and other dates in the chronologies. See Aquino et al. (2018) <doi:10.1007/s13253-018-0328-7>. Note that parts of the code underlying rplum are derived from the rbacon package by the same authors, and there remains a degree of overlap between the two packages.

Implementation of the Johnson Quantile-Parameterised Distribution in R. The Johnson Quantile-Parameterised Distribution (J-QPD) is a flexible distribution system that is parameterised by a symmetric percentile triplet of quantile values (typically the 10th-50th-90th) along with known support bounds for the distribution. The J-QPD system was developed by Hadlock and Bickel (2017) <doi:10.1287/deca.2016.0343>. This package implements the density, quantile, CDF and random number generator functions.

This package provides tools to analyze and visualize high-throughput metabolomics data acquired using chromatography-mass spectrometry. These tools preprocess data in a way that enables reliable and powerful differential analysis.

This package provides users not only with a function to readily calculate the higher-order partial and semi-partial correlations but also with statistics and p-values of the correlation coefficients.

This package implements an opinionated framework for building a production- ready Shiny application. Golem contains a series of tools like dependency management, version management, easy installation and deployment or documentation management.