gjamOrdination: Ordinate gjam data
In dbystrova/GJAM_clust: Generalized Joint Attribute Modeling

Description Usage Arguments Details Value Author(s) References See Also Examples

Ordinate data from a gjam object using correlation corresponding to reponse matrix E.

1 2	gjamOrdination(output, specLabs = NULL, col = NULL, cex = 1, PLOT=T, method = 'PCA')

`output`	object of `class` "gjam".
`specLabs`	`character vector` of variable names in `colnames(output$y)`.
`col`	`character vector` of columns in `output$y` to label in plots.
`cex`	text size in plot.
`PLOT`	`logical`, if true, draw plots.
`method`	`character` variable can specify `'NMDS'`.

Ordinates the response correlation ematrix contained in output$parameterTables. If method = 'PCA' returns eigenvalues and eigenvectors. If method = 'PCA' returns three NMDS dimensions. If PLOT, then plots will be generated. Uses principle components analysis or non-metric multidimensional scale (NMDS).

`eVecs`	`S x S` or, if there is an `other` response variable to be excluded, `S-1 x S-1` matrix of eigenvectors for species (rows) by eigenvectors (columns).
`eValues`	If `method = 'PCA'` returns length-`S` or, there is an `other` response variable to be excluded, length-`S-1` vector of eigenvalues. If `method = 'NMDS'` this variable is `NULL`.

James S Clark, jimclark@duke.edu

Clark, J.S., D. Nemergut, B. Seyednasrollah, P. Turner, and S. Zhang. 2017. Generalized joint attribute modeling for biodiversity analysis: Median-zero, multivariate, multifarious data. Ecological Monographs 87, 34-56.

gjam fits the data

A more detailed vignette is can be obtained with:

browseVignettes('gjam')

website 'http://sites.nicholas.duke.edu/clarklab/code/'.

## Not run: 
f      <- gjamSimData(S = 30, typeNames = 'CA') 
ml     <- list(ng = 30, burnin = 5, typeNames = f$typeNames, holdoutN = 10)
output <- gjam(f$formula, f$xdata, f$ydata, modelList = ml)
ePCA   <- gjamOrdination(output, PLOT=FALSE)
eNMDS  <- gjamOrdination(output, PLOT=FALSE, method='NMDS')

## End(Not run)