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mvabund: Statistical Methods for Analysing Multivariate Abundance Data

Authors

Yi Wang, Ulrike Naumann, Stephen Wright, Dirk Eddelbuettel and David Warton

License

LGPL (>= 2.1)

Installation

mvabund is available on CRAN.

The development version, with the latest bells and whistles, can be installed from GitHub using the devtools package:

devtools::install_github('aliceyiwang/mvabund')
library(mvabund)

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Version

Install

install.packages('mvabund')

Monthly Downloads

1,749

Version

4.1.12

License

LGPL (>= 2.1)

Maintainer

Last Published

May 28th, 2021

Functions in mvabund (4.1.12)

formulaUnimva

Create a List of Univariate Formulas
mvabund-package

Statistical methods for analysing multivariate abundance data
mvabund

Multivariate Abundance Data Objects
anova.manyglm

Analysis of Deviance for Multivariate Generalized Linear Model Fits for Abundance Data
anova.traitglm

Testing for a environment-by-trait (fourth corner) interaction by analysis of deviance
best.r.sq

Use R^2 to find the variables that best explain a multivariate response.
shiftpoints

Calculate a shift for plotting overlapping points
antTraits

Ant data, with species traits
boxplot.mvabund

Boxplots for multivariate abundance Data
mvformula

Model Formulae for Multivariate Abundance Data
manyglm

Fitting Generalized Linear Models for Multivariate Abundance Data
deviance.manylm

Model Deviance
manyany

Fitting Many Univariate Models to Multivariate Abundance Data
extend.x.formula

Extend a Formula to all of it's Terms
plot.manyany

Plot Diagnostics for a manyany or glm1path Object
tikus

Tikus Island Dataset
summary.manylm

Summarizing Linear Model Fits for Multivariate Abundance Data
coefplot.manyglm

Plots the coefficients of the covariates of a manyglm object with confidence intervals.
anova.manyany

Analysis of Deviance for Many Univariate Models Fitted to Multivariate Abundance Data
cv.glm1path

Fits a path of Generalised Linear Models with LASSO (or L1) penalties, and finds the best model by corss-validation.
ridgeParamEst

Estimation of the ridge parameter
Tasmania

Tasmania Dataset
residuals.manyglm

Residuals for MANYGLM, MANYANY, GLM1PATH Fits
plot.manylm

Plot Diagnostics for a manylm or a manyglm Object
predict.manylm

Model Predictions for Multivariate Linear Models
predict.traitglm

Predictions from fourth corner model fits
manylm

Fitting Linear Models for Multivariate Abundance Data
manylm.fit

workhose functions for fitting multivariate linear models
plot.mvabund

Plot Multivariate Abundance Data and Formulae
meanvar.plot

Construct Mean-Variance plots for Multivariate Abundance Data
anova.manylm

ANOVA for Linear Model Fits for Multivariate Abundance Data
solberg

Solberg Data
plotMvaFactor

Draw a Mvabund Object split into groups.
mvabund-internal

Internal mvabund Objects
predict.manyglm

Predict Method for MANYGLM Fits
spider

Spider data
glm1path

Fits a path of Generalised Linear Models with LASSO (or L1) penalties, and finds the model that minimises BIC.
logLik.manylm

Calculate the Log Likelihood
summary.manyglm

Summarizing Multivariate Generalized Linear Model Fits for Abundance Data
traitglm

Fits a fourth corner model for abundance as a function of environmental variables and species traits.
unabund

Remove the mvabund Class Attribute
glm1

Fits a Generalised Linear Models with a LASSO (or L1) penalty, given a value of the penalty parameter.