This package provides a coordinate descent algorithm for computing the solution paths of the sparse and coupled sparse asymmetric least squares, including the (adaptive) elastic net and Lasso penalized SALES and COSALES regressions.

This is an all-encompassing suite to facilitate the simulation of so-called quantities of interest by way of a multivariate normal distribution of the regression model's coefficients and variance-covariance matrix.

An interactive document on the topic of basic statistical analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/StatisticsPrimer/>.

iSEEu (the iSEE universe) contains diverse functionality to extend the usage of the iSEE package, including additional classes for the panels, or modes allowing easy configuration of iSEE applications.

The PLIER (Probe Logarithmic Error Intensity Estimate) method produces an improved signal by accounting for experimentally observed patterns in probe behavior and handling error at the appropriately at low and high signal values.

This package provides a simple interface to lat/long projection and datum transformation of the PROJ.4 cartographic projections library. It allows transformation of geographic coordinates from one projection and/or datum to another.

LIGER is a package for integrating and analyzing multiple single-cell datasets, developed and maintained by the Macosko lab. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors.

This package provides tools to generate a violin point plot, a combination of a violin/histogram plot and a scatter plot by offsetting points within a category based on their density using quasirandom noise.

This package provides a common framework for optimization of black-box functions for other packages, e.g. mlr3. It offers various optimization methods e.g. grid search, random search and generalized simulated annealing.

The rcshist utility displays the complete revision history of a set of RCS files including log messages and patches. It can also display the patch associated with a particular revision of an RCS file.

This package provides access to geocomputing and terrain analysis functions of the geographical information system (GIS) SAGA (System for Automated Geoscientific Analyses) from within R by running the command line version of SAGA. This package furthermore provides several R functions for handling ASCII grids, including a flexible framework for applying local functions (including predict methods of fitted models) and focal functions to multiple grids. SAGA GIS is available under GPL-2 / LGPL-2 licences from <https://sourceforge.net/projects/saga-gis/>.

This package provides streamlined functions for summarising and visualising regression models fitted with the rms package, in the preferred format for medical journals. The modelsummary_rms() function produces concise summaries for linear, logistic, and Cox regression models, including automatic handling of models containing restricted cubic spline (RCS) terms. The resulting summary dataframe can be easily converted into publication-ready documents using the flextable and officer packages. The ggrmsMD() function creates clear and customizable plots ('ggplot2 objects) to visualise RCS terms.

This package provides a build-time dependency for Cargo build scripts to assist in invoking the native C compiler to compile native C code into a static archive to be linked into Rust code.

Creating, rendering and writing BPMN diagrams <https://www.bpmn.org/>. Functionalities can be used to visualize and export BPMN diagrams created using the pm4py and bupaRminer packages. Part of the bupaR ecosystem.

This package performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>.

This package implements the convex clustering through majorization-minimization (CCMM) algorithm described in Touw, Groenen, and Terada (2022) <doi:10.48550/arXiv.2211.01877> to perform minimization of the convex clustering loss function.

The Discrete Transmuted Generalized Inverse Weibull (DTGIW) distribution is a new distribution for count data analysis. The DTGIW is discrete distribution based on Atchanut and Sirinapa (2021). <DOI: 10.14456/sjst-psu.2021.149>.

Manipulates date ('Date'), date time ('POSIXct') and time ('hms') vectors. Date/times are considered discrete and are floored whenever encountered. Times are wrapped and time zones are maintained unless explicitly altered by the user.

This package provides functions for (1) ranking, selecting, and prioritising genes, proteins, and metabolites from high dimensional biology experiments, (2) multivariate hit calling in high content screens, and (3) combining data from diverse sources.

Make it easy to create simplified trial summary (TS) domain based on FDA FDA guide <https://github.com/TuCai/phuse/blob/master/inst/examples/07_genTS/www/Simplified_TS_Creation_Guide_v2.pdf>.

Functional denoising and functional ANOVA through wavelet-domain Markov groves. Fore more details see: Ma L. and Soriano J. (2018) Efficient functional ANOVA through wavelet-domain Markov groves. <arXiv:1602.03990v2 [stat.ME]>.

This package provides a network-based gene weighting algorithm for pathway enrichment analysis, using either RNA-seq or microarray data. Zhaoyuan Fang, Weidong Tian and Hongbin Ji (2012) <doi:10.1038/cr.2011.149>.

Analyze small-sample clustered or longitudinal data using modified generalized estimating equations with bias-adjusted covariance estimator. The package provides any combination of three modified generalized estimating equations and 11 bias-adjusted covariance estimators.

This package provides a personalized dynamic latent factor model (Zhang et al. (2024) <doi:10.1093/biomet/asae015>) for irregular multi-resolution time series data, to interpolate unsampled measurements from low-resolution time series.