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.

Parametric Statistical Modelling and Inference for the 'spatstat' Family

Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test), confidence intervals for parameters, and prediction intervals for point counts. Model validation techniques include leverage, influence, partial residuals, added variable plots, diagnostic plots, pseudoscore residual plots, model compensators and Q-Q plots.

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.

NHS and Healthcare-Related Data for Education and Training

Free United Kingdom National Health Service (NHS) and other healthcare, or population health-related data for education and training purposes. This package contains synthetic data based on real healthcare datasets, or cuts of open-licenced official data. This package exists to support skills development in the NHS-R community: < https://nhsrcommunity.com/>.

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) .

Error Detection in Science

Test published summary statistics for consistency (Brown and Heathers, 2017, ; Allard, 2018, < https://aurelienallard.netlify.app/post/anaytic-grimmer-possibility-standard-deviations/>; Heathers and Brown, 2019, < https://osf.io/5vb3u/>). The package also provides infrastructure for implementing new error detection techniques.

'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) .