This package lets you generate random or human readable and pronounceable identifiers.

This package provides efficient functions for detecting multiple change points in multidimensional time series. The models can be piecewise constant or polynomial. Adaptive threshold selection methods are available, see Fan and Wu (2024) <arXiv:2403.00600>.

This package provides a friendly interface for the construction of regular expressions. Regular expressions are a very powerful feature, however they are often difficult to interpret. Rex allows you to build complex regular expressions from human readable expressions

This package provides a series of functions in some way considered useful to the author. These include methods for subsetting tables and generating indices for arrays, conditioning and intervening in probability distributions, generating combinations, fast transformations, and more...

Statistical analysis of static chamber concentration data for trace gas flux estimation.

Logger to keep track of informational events and errors useful for debugging.

R functions for the estimation and eigen-decomposition of multivariate autoregressive models.

This package provides a companion to the Chinese book ``Modern Statistical Graphics''.

Estimate False Discovery Rates (FDRs) for importance metrics from random forest runs.

Produce small area population estimates by fitting census data to survey data.

Create structured, formatted HTML tables of in a flexible and convenient way.

This package provides tools for categorical data analysis with complete or missing responses.

This package provides functions and data to construct technical trading rules with R.

This package offers an interactive function for the detection of breakpoints in series.

Implementation of a Recurrent Neural Network architectures in native R, including Long Short-Term Memory (Hochreiter and Schmidhuber, <doi:10.1162/neco.1997.9.8.1735>), Gated Recurrent Unit (Chung et al., <arXiv:1412.3555>) and vanilla RNN.

Regularized Greedy Forest wrapper of the Regularized Greedy Forest <https://github.com/RGF-team/rgf/tree/master/python-package> python package, which also includes a Multi-core implementation (FastRGF) <https://github.com/RGF-team/rgf/tree/master/FastRGF>.

This package performs analysis of polynomial regression in simple designs with quantitative treatments.

Genome-wide association analysis that accommodate membership information, variance adjustment, and correlated responses.

Calculates the normalized mutual information (NMI) of two community structures in network analysis.

Computes the studentized midrange distribution (pdf, cdf and quantile) and generates random numbers.

Generate Stochastic Branching Networks ('SBNs'). Used to model the branching structure of rivers.

This package provides tools for analysis of ChIP-seq and other functional sequencing data.

This package provides David Scott's ASH routines ported from S-PLUS to R.

This package provides an implementation of dimensionality reduction via regression using Kernel Ridge Regression.