Create and evaluate models using tidymodels and h2o <https://h2o.ai/>. The package enables users to specify h2o as an engine for several modeling methods.

Generalization of the Bayesian classification and regression tree (CART) model that partitions subjects into terminal nodes and tailors machine learning model to each terminal node.

Collection of tools to make R more convenient. Includes tools to summarize data using statistics not available with base R and manipulate objects for analyses.

This package provides functions and data sets reproducing some examples in Box, Hunter and Hunter II. Useful for statistical design of experiments, especially factorial experiments.

Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.

This package contains a time series classification method that obtains a set of filters that maximize the between-class and minimize the within-class distances.

Downloads the public data available from the Brazilian Access to Information Law and and performs a search on information requests and appeals made since 2015.

Interface with the Dat p2p network protocol <https://datproject.org>. Clone archives from the network, share your own files, and install packages from the network.

This package provides functions to calculate Divisia monetary aggregates index as given in Barnett, W. A. (1980) (<DOI:10.1016/0304-4076(80)90070-6>).

This package provides support for building Feldman-Cousins confidence intervals [G. J. Feldman and R. D. Cousins (1998) <doi:10.1103/PhysRevD.57.3873>].

These are two-sample tests for categorical data utilizing similarity information among the categories. They are useful when there is underlying structure on the categories.

Offers functions for the comparison of Gutenberg-Richter b-values. Several functions in GRTo are helpful for the assessment of the quality of seismicity catalogs.

Geostatistical analysis including variogram-based, likelihood-based and Bayesian methods. Software companion for Diggle and Ribeiro (2007) <doi:10.1007/978-0-387-48536-2>.

This package provides functions to access data from the US Department of Housing and Urban Development <https://www.huduser.gov/portal/dataset/fmr-api.html>.

An algorithm for time series analysis that leverages hidden Markov models, cluster analysis, and mixture distributions to segment data, detect patterns and predict future sequences.

The ISA is a biclustering algorithm that finds modules in an input matrix. A module or bicluster is a block of the reordered input matrix.

Estimate the slope and intercept of a bivariate linear relationship by calculating a posterior density that is invariant to interchange and scaling of the coordinates.

This package implements the methods described in Bond S, Farewell V, 2006, Exact Likelihood Estimation for a Negative Binomial Regression Model with Missing Outcomes, Biometrics.

This package provides a function for measuring the difference between two independent or non-independent empirical distributions and returning a significance level of the difference.

Includes functions and examples to compute NEAT, the Network Enrichment Analysis Test described in Signorelli et al. (2016, <DOI:10.1186/s12859-016-1203-6>).

Extends flexclust with an R implementation of order constrained solutions in k-means clustering (Steinley and Hubert, 2008, <doi:10.1007/s11336-008-9058-z>).

This package provides a semi-parametric estimation method for the Cox model with left-truncated data using augmented information from the marginal of truncation times.

Implementation of the pattern recognition technique Principal Component Pursuit tailored to environmental health data, as described in Gibson et al (2022) <doi:10.1289/EHP10479>.

Finds equivalence classes corresponding to a symmetric relation or undirected graph. Finds total order consistent with partial order or directed graph (so-called topological sort).