Methods for faster extraction (about 5x faster in a few test cases) of variance-covariance matrices and standard errors from models. Methods in the 'stats' package tend to rely on the summary method, which may waste time computing other summary statistics which are summarily ignored.

Estimating the disparity between two groups based on the extended model of the Peters-Belson (PB) method. Our model is the first work on the longitudinal data, and also can set a varying variable to find the complicated association between other variables and the varying variable. Our work is an extension of the Peters-Belson method which was originally published in Peters (1941)<doi:10.1080/00220671.1941.10881036> and Belson (1956)<doi:10.2307/2985420>.

Method to perform penalized variance component analysis.

Record test suite 'HTTP' requests and replays them during
    future runs. A port of the Ruby gem of the same name
    (<https://github.com/vcr/vcr/>). Works by recording real 'HTTP'
    requests/responses on disk in 'cassettes', and then replaying
    matching responses on subsequent requests.

Recursive partitioning for varying coefficient generalized linear models and ordinal linear mixed models. Special features are coefficient-wise partitioning, non-varying coefficients and partitioning of time-varying variables in longitudinal regression. A description of a part of this package was published by Burgin and Ritschard (2017) <doi:10.18637/jss.v080.i06>.

Defines new notions of prototype and size that are used to
    provide tools for consistent and well-founded type-coercion and
    size-recycling, and are in turn connected to ideas of type- and
    size-stability useful for analysing function interfaces.

A way of visualizing collections of time series and, optionally
    their future values, forecasts for their future values and prediction
    intervals for the forecasts. A web-based GUI can be used to display the
    information in a collection of time series.

Comparison of variance - covariance patterns using relative principal component analysis (relative eigenanalysis), as described in Le Maitre and Mitteroecker (2019) <doi:10.1111/2041-210X.13253>. Also provides functions to compute group covariance matrices, distance matrices, and perform proportionality tests. A worked sample on the body shape of cichlid fishes is included, based on the dataset from Kerschbaumer et al. (2013) <doi:10.5061/dryad.fc02f>.