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Hartigan's Dip Test Statistic for Unimodality - Corrected
Compute Hartigan's dip test statistic for unimodality / multimodality and provide a test with simulation based p-values, where the original public code has been corrected.
High-Dimensional Inference
Implementation of multiple approaches to perform inference in high-dimensional models.
Linear Mixed-Effects Models using 'Eigen' and S4
Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Generalized Nonlinear Models
Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others. Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.
Differential Evolution Optimization in Pure R
Differential Evolution (DE) stochastic heuristic algorithms for
global optimization of problems with and without general constraints.
The aim is to curate a collection of its variants that
(1) do not sacrifice simplicity of design,
(2) are essentially tuning-free, and
(3) can be efficiently implemented directly in the R language.
Currently, it provides implementations of the algorithms 'jDE' by
Brest et al. (2006)
Port of the S+ "Robust Library"
Methods for robust statistics, a state of the art in the early 2000s, notably for robust regression and robust multivariate analysis.
Density, Probability, Quantile ('DPQ') Computations
Computations for approximations and alternatives for the 'DPQ'
(Density (pdf), Probability (cdf) and Quantile) functions for probability
distributions in R.
Primary focus is on (central and non-central) beta, gamma and related
distributions such as the chi-squared, F, and t.
--
For several distribution functions, provide functions implementing formulas from
Johnson, Kotz, and Kemp (1992)
Local Polynomial (Ridge) Regression
Local Polynomial Regression with Ridging.
Data Sets from Mixed-Effects Models in S
Data sets and sample analyses from Pinheiro and Bates, "Mixed-effects Models in S and S-PLUS" (Springer, 2000).
Bayesian Applied Regression Modeling via Stan
Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.