Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models

Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics, 1989); including inference and basic methods. Some alternative algorithms to estimate "H".

Stable Distribution Functions

Density, Probability and Quantile functions, and random number generation for (skew) stable distributions, using the parametrizations of Nolan.

Normal aka Gaussian 1-d Mixture Models

Onedimensional Normal (i.e. Gaussian) Mixture Models (S3) Classes, for, e.g., density estimation or clustering algorithms research and teaching; providing the widely used Marron-Wand densities. Efficient random number generation and graphics. Fitting to data by efficient ML (Maximum Likelihood) or traditional EM estimation.

A Collection of Functions to Implement a Class for Univariate Polynomial Manipulations

A collection of functions to implement a class for univariate polynomial manipulations.

Multiple Precision Arithmetic

Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic).

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.

Computations and Approximations for Bessel Functions

Computations for Bessel function for complex, real and partly 'mpfr' (arbitrary precision) numbers; notably interfacing TOMS 644; approximations for large arguments, experiments, etc.

Companion to Applied Regression

Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.

Constrained B-Splines (Sparse Matrix Based)

Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming and Sparse Matrices.

Various R Programming Tools for Plotting Data

Various R programming tools for plotting data, including: - calculating and plotting locally smoothed summary function as ('bandplot', 'wapply'), - enhanced versions of standard plots ('barplot2', 'boxplot2', 'heatmap.2', 'smartlegend'), - manipulating colors ('col2hex', 'colorpanel', 'redgreen', 'greenred', 'bluered', 'redblue', 'rich.colors'), - calculating and plotting two-dimensional data summaries ('ci2d', 'hist2d'), - enhanced regression diagnostic plots ('lmplot2', 'residplot'), - formula-enabled interface to 'stats::lowess' function ('lowess'), - displaying textual data in plots ('textplot', 'sinkplot'), - plotting dots whose size reflects the relative magnitude of the elements ('balloonplot', 'bubbleplot'), - plotting "Venn" diagrams ('venn'), - displaying Open-Office style plots ('ooplot'), - plotting multiple data on same region, with separate axes ('overplot'), - plotting means and confidence intervals ('plotCI', 'plotmeans'), - spacing points in an x-y plot so they don't overlap ('space').