This package provides access to a suite of geospatial data layers for wildfire management, fuel modeling, ecology, natural resource management, climate, conservation, etc., via the LANDFIRE (<https://www.landfire.gov/>) Product Service ('LFPS') API.

This package provides functions for the complete analysis of respiratory data. Consists of a set of functions that allow to preprocessing respiratory data, calculate both regular statistics and nonlinear statistics, conduct group comparison and visualize the results. Especially, Power Spectral Density ('PSD') (A. Eke (2000) <doi:10.1007/s004249900135>), MultiScale Entropy(MSE) ('Madalena Costa(2002) <doi:10.1103/PhysRevLett.89.068102>) and MultiFractal Detrended Fluctuation Analysis(MFDFA) ('Jan W.Kantelhardt (2002) <doi:10.1016/S0378-4371(02)01383-3>) were applied for the analysis of respiratory data.

This package implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Random-projection ensemble classification, J. Roy. Statist. Soc., Ser. B. (with discussion), 79, 959--1035". The random projection ensemble classifier is a general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.

We develop the entire solution paths for ROC-SVM presented by Rakotomamonjy. The ROC-SVM solution path algorithm greatly facilitates the tuning procedure for regularization parameter, lambda in ROC-SVM by avoiding grid search algorithm which may be computationally too intensive. For more information on the ROC-SVM, see the report in the ROC Analysis in AI workshop(ROCAI-2004) : Hernà ndez-Orallo, José, et al. (2004) <doi:10.1145/1046456.1046489>.

This package provides a set of tools to explore the behaviour statistics used for forensic DNA interpretation when close relatives are involved. The package also offers some useful tools for exploring other forensic DNA situations.

Compiles C++ code using Rcpp <doi:10.18637/jss.v040.i08>, Eigen <doi:10.18637/jss.v052.i05> and CppAD to produce first and second order partial derivatives. Also provides an implementation of Faa di Bruno's formula to combine the partial derivatives of composed functions.

Assists in the whole process of designing and evaluating Randomized Control Trials. Robust treatment assignment by strata/blocks, that handles misfits; Power calculations of the minimum detectable treatment effect or minimum populations; Balance tables of T-test of covariates; Balance Regression: (treatment ~ all x variables) with F-test of null model; Impact_evaluation: Impact evaluation regressions. This function gives you the option to include control_vars, fixed effect variables, cluster variables (for robust SE), multiple endogenous variables and multiple heterogeneous variables (to test treatment effect heterogeneity) summary_statistics: Function that creates a summary statistics table with statistics rank observations in n groups: Creates a factor variable with n groups. Each group has a min and max label attach to each category. Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.

An algorithm is proposed to estimate regression kink model proposed by the paper, Lixiong Yang and Jen-Je Su (2018) <doi:10.1016/j.jimonfin.2018.06.002>.

Blaze is an open-source, high-performance C++ math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and ease of use of a domain-specific language with HPC-grade performance, making it one of the most intuitive and fastest C++ math libraries available. The RcppBlaze package includes the header files from the Blaze library with disabling some functionalities related to link to the thread and system libraries which make RcppBlaze be a header-only library. Therefore, users do not need to install Blaze'.

This package performs genome-wide association studies (GWAS) on individuals that are both related and have repeated measurements. For each Single Nucleotide Polymorphism (SNP), it computes score statistic based p-values for a linear mixed model including random polygenic effects and a random effect for repeated measurements. The computed p-values can be visualized in a Manhattan plot. For more details see Ronnegard et al. (2016) <doi:10.1111/2041-210X.12535> and for more examples see <https://github.com/larsronn/RepeatABEL_Tutorials>.

This package provides estimation and data generation tools for several new regression models, including the gamma, beta, inverse gamma and beta prime distributions. These models can be parameterized based on the mean, median, mode, geometric mean and harmonic mean, as specified by the user. For details, see Bourguignon and Gallardo (2025a) <doi:10.1016/j.chemolab.2025.105382> and Bourguignon and Gallardo (2025b) <doi:10.1111/stan.70007>.

Create and manipulate hypergraph objects. This early version of rhype allows for the output of matrices associated with the hypergraphs themselves. It also uses these matrices to calculate hypergraph spectra and perform spectral comparison. Functionality coming soon includes calculation of hyperpaths and hypergraph centrality measures.

Non-inferiority test and diagnostic test are very important in clinical trails. This package is to get a p value from the non-inferiority test for ROC curves from diagnostic test.

An implementation of the Heroicons icon library for shiny applications and other R web-based projects. You can search, render, and customize icons without CSS or JavaScript dependencies.

Computes the ridge partial correlation coefficients in a high or ultra-high dimensional linear regression problem. An extended Bayesian information criterion is also implemented for variable selection. Users provide the matrix of covariates as a usual dense matrix or a sparse matrix stored in a compressed sparse column format. Detail of the method is given in the manual.

Utilities to access Integrated Food Security Phase Classification (IPC) and Cadre Harmonisé (CH) food security data. Wrapper functions are available for all of the IPC-CH Public API (<https://docs.api.ipcinfo.org>) simplified and advanced endpoints to easily download the data in a clean and tidy format.

This package performs exploratory projection pursuit via REPPlab (Daniel Fischer, Alain Berro, Klaus Nordhausen & Anne Ruiz-Gazen (2019) <doi:10.1080/03610918.2019.1626880>) using a Shiny app.

Converts LESS to CSS. It uses V8 engine, where LESS parser is run. Functions for LESS text, file or folder conversion are provided. This work was supported by a junior grant research project by Czech Science Foundation GACR no. GJ18-04150Y'.

Enhances the R Optimization Infrastructure ('ROI') package with the possibility to obtain multiple solutions for linear problems with binary variables. The main function is copied (with small modifications) from the relations package.

Allow for easy-to-use testing or evaluating of linear equality and inequality restrictions about parameters and effects in (generalized) linear statistical models.

Build regular expressions piece by piece using human readable code. This package is designed for interactive use. For package development, use the rebus.* dependencies.

Simple, easy to use, and flexible functionality for recoding variables. It allows for simple piecewise definition of transformations.

This package provides methods to easily build requests in the non-standard JSON schema required by the National Institute of Health (NIH)'s RePORTER Project API <https://api.reporter.nih.gov/#/Search/post_v2_projects_search>. Also retrieve and process result sets as either a ragged or flattened tibble'.

IUCN Red List (<https://api.iucnredlist.org/>) client. The IUCN Red List is a global list of threatened and endangered species. Functions cover all of the Red List API routes. An API key is required.