Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

Analyze and model heteroskedastic behavior in financial time series.

Kernel Regression Smoothing with Local or Global Plug-in Bandwidth

Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.

'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) .

Quantile Regression

Estimation and inference methods for models for conditional quantile functions: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press, and Koenker, R. et al. (2017) Handbook of Quantile Regression, CRC Press, .

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) for single-objective optimization and 'NCDE' by Qu et al. (2012) for multimodal optimization (single-objective problems with multiple solutions).

DPQ (Density, Probability, Quantile) Distribution Computations using MPFR

An extension to the 'DPQ' package with computations for 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions, where the functions here partly use the 'Rmpfr' package and hence the underlying 'MPFR' and 'GMP' C libraries.

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) and Johnson, Kotz, and Balakrishnan (1995) for discrete or continuous distributions respectively. This is for the use of researchers in these numerical approximation implementations, notably for my own use in order to improve standard R pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}.

Local Polynomial (Ridge) Regression

Local Polynomial Regression with Ridging.

Embedded Conic Solver in R

R interface to the Embedded COnic Solver (ECOS), an efficient and robust C library for convex problems. Conic and equality constraints can be specified in addition to integer and boolean variable constraints for mixed-integer problems. This R interface is inspired by the python interface and has similar calling conventions.