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Utilities from 'Seminar fuer Statistik' ETH Zurich
Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, some of which were ported from S-plus in the 1990s. For graphics, have pretty (Log-scale) axes eaxis(), an enhanced Tukey-Anscombe plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', pretty arrows, etc. For robustness, have a robust F test and robust range(). For system support, notably on Linux, provides 'Sys.*()' functions with more access to system and CPU information. Finally, miscellaneous utilities such as simple efficient prime numbers, integer codes, Duplicated(), toLatex.numeric() and is.whole().
Ordination and Multivariate Analysis for Ecology
A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.
Flexible Mixture Modeling
A general framework for finite mixtures of regression models using the EM algorithm is implemented. The E-step and all data handling are provided, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.
Indices of Effect Size
Provide utilities to work with indices of effect size for a wide
variety of models and hypothesis tests (see list of supported models using
the function 'insight::supported_models()'), allowing computation of and
conversion between indices such as Cohen's d, r, odds, etc.
References: Ben-Shachar et al. (2020)
Forecasting Mortality, Fertility, Migration and Population Data
Functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.
SIMEX- And MCSIMEX-Algorithm for Measurement Error Models
Implementation of the SIMEX-Algorithm by Cook & Stefanski (1994)
Relative Distribution Methods
Tools for the comparison of distributions. This includes nonparametric estimation of the relative distribution PDF and CDF and numerical summaries as described in "Relative Distribution Methods in the Social Sciences" by Mark S. Handcock and Martina Morris, Springer-Verlag, 1999, Springer-Verlag, ISBN 0387987789.
Tidying Methods for Mixed Models
Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Convert Statistical Objects into Tidy Tibbles
Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Statistical Methods for Analysing Multivariate Abundance Data
A set of tools for displaying, modeling and analysing multivariate abundance data in community ecology. See 'mvabund-package.Rd' for details of overall package organization. The package is implemented with the Gnu Scientific Library (< http://www.gnu.org/software/gsl/>) and 'Rcpp' (< http://dirk.eddelbuettel.com/code/rcpp.html>) 'R' / 'C++' classes.