ecostats: Code and Data Accompanying the Eco-Stats Text (Warton 2022) (original) (raw)

Functions and data supporting the Eco-Stats text (Warton, 2022, Springer), and solutions to exercises. Functions include tools for using simulation envelopes in diagnostic plots, and a function for diagnostic plots of multivariate linear models. Datasets mentioned in the package are included here (where not available elsewhere) and there is a vignette for each chapter of the text with solutions to exercises.

Version: 1.2.2
Depends: R (≥ 3.5.0), mvabund (≥ 4.2)
Imports: ecoCopula, GET, graphics, grDevices, MASS, methods, mgcv, mvtnorm, parallel, stats
Suggests: knitr, rmarkdown, ade4, caper, car, corrplot, DAAG, DHARMa, dplyr, gclus, GGally, ggplot2, ggthemes, glmnet, gllvm, glmmTMB, GPArotation, grplasso, lattice, leaps, lme4, MCMCglmm, multcomp, nlme, ordinal, permute, pgirmess, phylobase, phylosignal, psych, reshape2, smatr, testthat, vegan, VGAM, covr
Published: 2025-06-06
DOI: 10.32614/CRAN.package.ecostats
Author: David Warton [aut, cre], Christopher Chung [ctb], Mark Donoghoe [ctb], Eve Slavich [ctb]
Maintainer: David Warton <david.warton at unsw.edu.au>
License: LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2.1)]
URL: https://dwarton.github.io/ecostats/
NeedsCompilation: no
Materials: README
CRAN checks: ecostats results

Documentation:

Reference manual: ecostats.html , <ecostats.pdf>
Vignettes: Chapter 10 – Analysing discrete data – Exercise solutions and Code Boxes (source) Chapter 11 – Multivariate analysis – Exercise solutions and Code Boxes (source) Chapter 12 – Visualising many responses – Exercise solutions and Code Boxes (source) Chapter 13 – Allometric line-fitting – Exercise solutions and Code Boxes (source, R code) Chapter 14 – Multivariate abundances – inference about environmental associations – Exercise solutions and Code Boxes (source) Chapter 15 – Predicting multivariate abundances – Exercise solutions and Code Boxes (source) Chapter 16 – Understanding variation in environmental response across taxa – Exercise solutions and Code Boxes (source) Chapter 17 – Studying co-occurrence patterns – Exercise solutions and Code Boxes (source, R code) Chapter 1 – 'STATS 101' Revision – Exercise solutions and Code Boxes (source, R code) Chapter 2 – An importance equivalence result – Exercise solutions and Code Boxes (source, R code) Chapter 3 – Regression with multiple predictor variables – Exercise solutions and Code Boxes (source) Chapter 4 – Linear models – anything goes – Exercise solutions and Code Boxes (source) Chapter 5 – Model selection – Exercise solutions and Code Boxes (source) Chapter 6 – Mixed effect models – Exercise solutions and Code Boxes (source, R code) Chapter 7 – Correlated samples in times, space, phylogeny... – Exercise solutions and Code Boxes (source) Chapter 8 – Wiggly Models – Exercise solutions and Code Boxes (source, R code) Chapter 9 – Design-based inference – Exercise solutions and Code Boxes (source) Eco-Stats – Code and Data Accompanying the Eco-Stats Text (source, R code)

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