Given raster files directly downloaded from various websites, it generates a raster structure where it merges them if they are tiles of the same scene and classifies them according to their spectral and spatial resolution for easy access by name.

This package provides a set of reliable routines to ease semiparametric survival regression modeling based on Bernstein polynomials. spsurv includes proportional hazards, proportional odds and accelerated failure time frameworks for right-censored data. RV Panaro (2020) <arXiv:2003.10548>.

This package provides a simple interface to search available data provided by Theia (<https://theia.cnes.fr>), download it, and manage it. Data can be downloaded based on a search result or from a cart file downloaded from Theia website.

This package implements differential language analysis with statistical tests and offers various language visualization techniques for n-grams and topics. It also supports the text package. For more information, visit <https://r-topics.org/> and <https://www.r-text.org/>.

Simulation, exploratory data analysis and Bayesian analysis of the p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) <doi:10.1080/00949655.2020.1754819>.

Lefser is an implementation in R of the popular "LDA Effect Size" (LEfSe) method for microbiome biomarker discovery. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers of groups and sub-groups.

This package provides a functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions.

This package provides a data.table backend for dplyr. The goal of dtplyr is to allow you to write dplyr code that is automatically translated to the equivalent, but usually much faster, data.table code.

This package provides procedures to answer the following questions: How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have?

This package is a collection of miscellaneous utility functions, supporting data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a tidyverse workflow.

Algorithms to price American and European equity options, convertible bonds and a variety of other financial derivatives. It uses an extension of the usual Black-Scholes model in which jump to default may occur at a probability specified by a power-law link between stock price and hazard rate as found in the paper by Takahashi, Kobayashi, and Nakagawa (2001) <doi:10.3905/jfi.2001.319302>. We use ideas and techniques from Andersen and Buffum (2002) <doi:10.2139/ssrn.355308> and Linetsky (2006) <doi:10.1111/j.1467-9965.2006.00271.x>.

This package performs wood cell anatomical data analyses on spatially explicit xylem (tracheids) datasets derived from thin sections of woody tissue. The package includes functions for visualisation, detection and alignment of continuous tracheid radial file (defined as rows) and individual tracheid position within an annual ring of coniferous species. This package is designed to be used with elaborate cell output, e.g. as provided with ROXAS (von Arx & Carrer, 2014 <doi:10.1016/j.dendro.2013.12.001>). The package has been validated for Picea abies, Larix Siberica, Pinus cembra and Pinus sylvestris.

The regression-based (RB) approach is a method to test the missing data mechanism. This package contains two functions that test the type of missing data (Missing Completely At Random vs Missing At Random) on the basis of the RB approach. The first function applies the RB approach independently on each variable with missing data, using the completely observed variables only. The second function tests the missing data mechanism globally (on all variables with missing data) with the use of all available information. The algorithm is adapted both to continuous and categorical data.

The ROCm System Management Interface Library, or ROCm SMI library, is part of the Radeon Open Compute ROCm software stack. It is a C library for Linux that provides a user space interface for applications to monitor and control GPU applications.

Lightweight validation tool for checking function arguments and validating data analysis scripts. This is an alternative to stopifnot() from the base package and to assert_that() from the assertthat package. It provides more informative error messages and facilitates debugging.

This package provides WHO Child Growth Standards (z-scores) with confidence intervals and standard errors around the prevalence estimates, taking into account complex sample designs. More information on the methods is available online: <https://www.who.int/tools/child-growth-standards>.

Dose-response modeling for negative-binomial distributed data with a variety of dose-response models. Covariate adjustment and Bayesian model averaging is supported. Functions are provided to easily obtain inference on the dose-response relationship and plot the dose-response curve.

This package provides functions to produce some circular plots for circular data, in a height- or area-proportional manner. They include bar plots, smooth density plots, stacked dot plots, histograms, multi-class stacked smooth density plots, and multi-class stacked histograms.

This package provides a clustered random forest algorithm for fitting random forests for data of independent clusters, that exhibit within cluster dependence. Details of the method can be found in Young and Buehlmann (2025) <doi:10.48550/arXiv.2503.12634>.

This package provides functions for nonlinear regression parameters estimation by algorithms based on Controlled Random Search algorithm. Both functions (crs4hc(), crs4hce()) adapt current search strategy by four heuristics competition. In addition, crs4hce() improves adaptability by adaptive stopping condition.

Differential Analysis of short RNA transcripts that can be modeled by either Poisson or Negative binomial distribution. The statistical methodology implemented in this package is based on the random selection of references genes (Desaulle et al. (2021) <arXiv:2103.09872>).

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.

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.