Functions to Fit Mixtures of Regressions

Fits mixtures of (possibly multivariate) regressions (which has been described as doing ANCOVA when you don't know the levels). Turner (2000) .

Sparse Three-Dimensional Arrays and Linear Algebra Utilities

Defines sparse three-dimensional arrays and supports standard operations on them. The package also includes utility functions for matrix calculations that are common in statistics, such as quadratic forms.

Quasi Analysis of Variance for K-Functions

One-way and two-way analysis of variance for replicated point patterns, grouped by one or two classification factors, on the basis of the corresponding K-functions.

Tools for Analysis, Design, and Operation of Water Supply Storages

Measure single-storage water supply system performance using resilience, reliability, and vulnerability metrics; assess storage-yield-reliability relationships; determine no-fail storage with sequent peak analysis; optimize release decisions for water supply, hydropower, and multi-objective reservoirs using deterministic and stochastic dynamic programming; generate inflow replicates using parametric and non-parametric models; evaluate inflow persistence using the Hurst coefficient.

Translate ICD-9 into Injury Severity Score

Calculate the injury severity score (ISS) based on the dictionary in 'ICDPIC' from < https://ideas.repec.org/c/boc/bocode/s457028.html>. The original code was written in 'STATA 11'. The original 'STATA' code was written by David Clark, Turner Osler and David Hahn. I implement the same logic for easier access. Ref: David E. Clark & Turner M. Osler & David R. Hahn, 2009. "ICDPIC: Stata module to provide methods for translating International Classification of Diseases (Ninth Revision) diagnosis codes into standard injury categories and/or scores," Statistical Software Components S457028, Boston College Department of Economics, revised 29 Oct 2010.

Practical 'R' Packaging in 'Docker'

Streamline the creation of 'Docker' images with 'R' packages and dependencies embedded. The 'pracpac' package provides a 'usethis'-like interface to creating Dockerfiles with dependencies managed by 'renv'. The 'pracpac' functionality is described in Nagraj and Turner (2023) .

'eXtra' / 'eXperimental' Functionality for Robust Statistics

Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary' Functionality for Robust Statistics. Hence methods which are not well established, often related to methods in package 'robustbase'. Amazingly, 'BACON()', originally by Billor, Hadi, and Velleman (2000) has become established in places. The "barrow wheel" `rbwheel()` is from Stahel and Mächler (2009) .

Hidden Markov Models with Discrete Non-Parametric Observation Distributions

Fits hidden Markov models with discrete non-parametric observation distributions to data sets. The observations may be univariate or bivariate. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model. Auxiliary predictors are accommodated in the univariate setting.

Vegetated Filter Strip and Erosion Model

Empirical models for runoff, erosion, and phosphorus loss across a vegetated filter strip, given slope, soils, climate, and vegetation (Gall et al., 2018) . It also includes functions for deriving climate parameters from measured daily weather data, and for simulating rainfall. Models implemented include MUSLE (Williams, 1975) and APLE (Vadas et al., 2009 ).

Discretised Beta Distribution

Tools for working with a new versatile discrete distribution, the db ("discretised Beta") distribution. This package provides density (probability), distribution, inverse distribution (quantile) and random data generation functions for the db family. It provides functions to effect conveniently maximum likelihood estimation of parameters, and a variety of useful plotting functions. It provides goodness of fit tests and functions to calculate the Fisher information, different estimates of the hessian of the log likelihood and Monte Carlo estimation of the covariance matrix of the maximum likelihood parameter estimates. In addition it provides analogous tools for working with the beta-binomial distribution which has been proposed as a competitor to the db distribution.