mvabund v4.0.1
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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.
Readme
mvabund 
=======
Statistical Methods for Analysing Multivariate Abundance Data
Authors
Yi Wang, Ulrike Naumann, Stephen Wright, Dirk Eddelbuettel and David Warton
License
LGPL (>= 2.1)
Functions in mvabund
| Name | Description | |
| coefplot.manyglm | Plots the coefficients of the covariates of a manyglm object with confidence intervals. | |
| manylm | Fitting Linear Models for Multivariate Abundance Data | |
| manylm.fit | workhose functions for fitting multivariate linear models | |
| mvformula | Model Formulae for Multivariate Abundance Data | |
| plot.manyany | Plot Diagnostics for a manyany or glm1path Object | |
| Tasmania | Tasmania Dataset | |
| anova.manyany | Analysis of Deviance for Many Univariate Models Fitted to Multivariate Abundance Data | |
| residuals.manyglm | Residuals for MANYGLM, MANYANY, GLM1PATH Fits | |
| ridgeParamEst | Estimation of the ridge parameter | |
| formulaUnimva | Create a List of Univariate Formulas | |
| glm1path | Fits a path of Generalised Linear Models with LASSO (or L1) penalties, and finds the model that minimises BIC. | |
| glm1 | Fits a Generalised Linear Models with a LASSO (or L1) penalty, given a value of the penalty parameter. | |
| mvabund | Multivariate Abundance Data Objects | |
| mvabund-package | Statistical methods for analysing multivariate abundance data | |
| logLik.manylm | Calculate the Log Likelihood | |
| spider | Spider data | |
| summary.manyglm | Summarizing Multivariate Generalized Linear Model Fits for Abundance Data | |
| plotMvaFactor | Draw a Mvabund Object split into groups. | |
| predict.manyglm | Predict Method for MANYGLM Fits | |
| anova.manyglm | Analysis of Deviance for Multivariate Generalized Linear Model Fits for Abundance Data | |
| anova.manylm | ANOVA for Linear Model Fits for Multivariate Abundance Data | |
| plot.manylm | Plot Diagnostics for a manylm or a manyglm Object | |
| anova.traitglm | Testing for a environment-by-trait (fourth corner) interaction by analysis of deviance | |
| plot.mvabund | Plot Multivariate Abundance Data and Formulae | |
| predict.manylm | Model Predictions for Multivariate Linear Models | |
| antTraits | Ant data, with species traits | |
| predict.traitglm | Predictions from fourth corner model fits | |
| manyany | Fitting Many Univariate Models to Multivariate Abundance Data | |
| manyglm | Fitting Generalized Linear Models for Multivariate Abundance Data | |
| shiftpoints | Calculate a shift for plotting overlapping points | |
| solberg | Solberg Data | |
| traitglm | Fits a fourth corner model for abundance as a function of environmental variables and species traits. | |
| unabund | Remove the mvabund Class Attribute | |
| best.r.sq | Use R^2 to find the variables that best explain a multivariate response. | |
| boxplot.mvabund | Boxplots for multivariate abundance Data | |
| deviance.manylm | Model Deviance | |
| extend.x.formula | Extend a Formula to all of it's Terms | |
| meanvar.plot | Construct Mean-Variance plots for Multivariate Abundance Data | |
| mvabund-internal | Internal mvabund Objects | |
| summary.manylm | Summarizing Linear Model Fits for Multivariate Abundance Data | |
| tikus | Tikus Island Dataset | |
| cv.glm1path | Fits a path of Generalised Linear Models with LASSO (or L1) penalties, and finds the best model by corss-validation. | |
| No Results! | ||
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Details
| Date | 2019-01-07 |
| Encoding | UTF-8 |
| LinkingTo | Rcpp, RcppGSL |
| License | LGPL (>= 2.1) |
| NeedsCompilation | yes |
| Packaged | 2019-01-07 02:40:20 UTC; z3103495 |
| RoxygenNote | 6.0.1 |
| Repository | CRAN |
| Date/Publication | 2019-01-07 17:00:11 UTC |
| imports | MASS , methods , parallel , Rcpp , statmod , stats , tweedie |
| depends | R (>= 3.0.0) |
| linkingto | RcppGSL |
| suggests | testthat |
| Contributors | Dirk Eddelbuettel, Yi Wang, Ulrike Naumann, Stephen Wright, Ian Renner, Jenni Niku, Julian Byrnes, Ralph dos Santos Silva, John Wilshire |
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