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

This package provides a collection of ROI optimization problems based on the NETLIB-LP collection. Netlib is a software repository, which amongst many other software for scientific computing contains a collection of linear programming problems. The purpose of this package is to make this problems easily accessible from R as ROI optimization problems.

This package provides a supportive collection of functions for gathering and plotting treatment ranking metrics after network meta-analysis.

Process phylogenetic trees with tropical support vector machine and principal component analysis defined with tropical geometry. Details about tropical support vector machine are available in : Tang, X., Wang, H. & Yoshida, R. (2020) <arXiv:2003.00677>. Details about tropical principle component analysis are available in : Page, R., Yoshida, R. & Zhang L. (2020) <doi:10.1093/bioinformatics/btaa564> and Yoshida, R., Zhang, L. & Zhang, X. (2019) <doi:10.1007/s11538-018-0493-4>.

Automatically flags common spatial errors in biological collection data using metadata and specialists information. RuHere implements a workflow to manage occurrence data through six steps: dataset merging, metadata flagging, validation against expert-derived distribution maps, visualization of flagged records, and sampling bias exploration. It specifically integrates specialist-curated range information to identify geographic errors and introductions that often escape standard automated validation procedures. For details on the methodology, see: Trindade & Caron (2026) <doi:10.64898/2026.02.02.703373>.

The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways via a rich API. This API was preceded by an earlier version which has been deprecated since 2010 (but is still supported to provide backwards compatibility in the package RcppClassic'). This package RcppClassicExamples provides usage examples for the older, deprecated API. There is also a corresponding package RcppExamples with examples for the newer, current API which we strongly recommend as the basis for all new development.

HydroBudget is a spatially distributed groundwater recharge model that computes a superficial water budget on grid cells with outputs aggregated into monthly time steps. It was developed as an accessible and computationally affordable model to simulate groundwater recharge over large areas (thousands of km2, regional-scale watersheds) and for long time periods (decades), in cold and humid climates. Model algorithms are based on the research of Dubois, E. et al. (2021a) <doi:10.5683/SP3/EUDV3H> and Dubois, E. et al. (2021b) <doi:10.5194/hess-25-6567-2021>.

An implementation of algorithms for estimation of the graphical lasso regularization parameter described in Pedro Cisneros-Velarde, Alexander Petersen and Sang-Yun Oh (2020) <http://proceedings.mlr.press/v108/cisneros20a.html>.

Compute spatially explicit land-use metrics for stream survey sites in GRASS GIS and R as an open-source implementation of IDW-PLUS (Inverse Distance Weighted Percent Land Use for Streams). The package includes functions for preprocessing digital elevation and streams data, and one function to compute all the spatially explicit land use metrics described in Peterson et al. (2011) <doi:10.1111/j.1365-2427.2010.02507.x> and previously implemented by Peterson and Pearse (2017) <doi:10.1111/1752-1688.12558> in ArcGIS-Python as IDW-PLUS.

Uses convolution-based techniques to generate simulated camera bokeh, depth of field, and other camera effects, using an image and an optional depth map. Accepts both filename inputs and in-memory array representations of images and matrices, including common raster formats such as JPEG', PNG', TIFF', TGA', BMP', PSD', GIF', HDR', PIC', PNM', DNG', and EXR'. Includes functions to perform 2D convolutions, color correction, colorspace conversion, image/matrix reorientation and resizing, image and text overlays, exposure adjustment, camera vignette effects, and image titles.

Duplicated restaurant data (pre-processed and formatted) for entity resolution. This package contains formatted data from a data set that contains information about different restaurants, with the Zagats portion containing 331 records and the Fodors portion containing 533 records. The following variables are included in the data set: id, name, address, city, phone, type. The data set has a respective gold data set that provides information on which records match based on id.

It is widely documented in psychology, economics and other disciplines that socio-economic agent may not pay full attention to all available alternatives, rendering standard revealed preference theory invalid. This package implements the estimation and inference procedures of Cattaneo, Ma, Masatlioglu and Suleymanov (2020) <arXiv:1712.03448> and Cattaneo, Cheung, Ma, and Masatlioglu (2022) <arXiv:2110.10650>, which utilizes standard choice data to partially identify and estimate a decision maker's preference and attention. For inference, several simulation-based critical values are provided.

Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.

Build regular expressions using grammar and functionality inspired by <https://github.com/VerbalExpressions>. Usage of the %>% is encouraged to build expressions in a chain-like fashion.

An implementation of the RaCE-NMA (Rank-Clustered Estimation for Network Meta-Analysis) model for post-hoc clustering of treatments or interventions by rank in network meta-analysis data. Functions for model estimation, assessment, and displaying results are provided. For more details, see Pearce and Zhou (2025) <doi:10.1017/rsm.2025.10049>.

Display spatial data with interactive maps powered by the open- source JavaScript library Leaflet (see <https://leafletjs.com/>). Maps can be rendered in a web browser or displayed in the HTML viewer pane of RStudio'. This package is designed to be easy to use and can create complex maps with vector and raster data, web served map tiles and interface elements.

This package provides a rolling version of the Latent Dirichlet Allocation, see Rieger et al. (2021) <doi:10.18653/v1/2021.findings-emnlp.201>. By a sequential approach, it enables the construction of LDA-based time series of topics that are consistent with previous states of LDA models. After an initial modeling, updates can be computed efficiently, allowing for real-time monitoring and detection of events or structural breaks.

Set of functions that enable you to use the FUSION commands (Program available in: <http://forsys.sefs.uw.edu/fusion/fusionlatest.html>).

Multivariate optimal allocation for different domains in one and two stages stratified sample design. R2BEAT extends the Neyman (1934) â Tschuprow (1923) allocation method to the case of several variables, adopting a generalization of the Bethelâ s proposal (1989). R2BEAT develops this methodology but, moreover, it allows to determine the sample allocation in the multivariate and multi-domains case of estimates for two-stage stratified samples. It also allows to perform both Primary Stage Units and Secondary Stage Units selection. This package requires the availability of ReGenesees', that can be installed from <https://github.com/DiegoZardetto/ReGenesees>.

Cloth Simulation Filter (CSF) is an airborne LiDAR (Light Detection and Ranging) ground points filtering algorithm which is based on cloth simulation. It tries to simulate the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface <https://www.mdpi.com/2072-4292/8/6/501/htm>.

Robust kernel center matrix, robust kernel cross-covariance operator for kernel unsupervised methods, kernel canonical correlation analysis, influence function of identifying significant outliers or atypical objects from multimodal datasets. Alam, M. A, Fukumizu, K., Wang Y.-P. (2018) <doi:10.1016/j.neucom.2018.04.008>. Alam, M. A, Calhoun, C. D., Wang Y.-P. (2018) <doi:10.1016/j.csda.2018.03.013>.

This package provides functions for semi-automated quality control of bulk RNA-seq data.

Define distribution families and fit them to interval-censored and interval-truncated data, where the truncation bounds may depend on the individual observation. The defined distributions feature density, probability, sampling and fitting methods as well as efficient implementations of the log-density log f(x) and log-probability log P(x0 <= X <= x1) for use in TensorFlow neural networks via the tensorflow package. Allows training parametric neural networks on interval-censored and interval-truncated data with flexible parameterization. Applications include Claims Development in Non-Life Insurance, e.g. modelling reporting delay distributions from incomplete data, see Bücher, Rosenstock (2022) <doi:10.1007/s13385-022-00314-4>.

This package provides tools for linear, nonlinear and nonparametric regression and classification. Novel graphical methods for assessment of parametric models using nonparametric methods. One vs. All and All vs. All multiclass classification, optional class probabilities adjustment. Nonparametric regression (k-NN) for general dimension, local-linear option. Nonlinear regression with Eickert-White method for dealing with heteroscedasticity. Utilities for converting time series to rectangular form. Utilities for conversion between factors and indicator variables. Some code related to "Statistical Regression and Classification: from Linear Models to Machine Learning", N. Matloff, 2017, CRC, ISBN 9781498710916.