gjamOrdination {gjam}

Ordinate gjam data

Description

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

Usage

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

Arguments

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'.

Details

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).

Value

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.

Author(s)

James S Clark, [e-mail]

References

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.

See Also

gjam fits the data

A more detailed vignette is can be obtained with:

browseVignettes('gjam')

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

Examples

## Not run: 
f      <- gjamSimData(S = 30, typeNames = 'CA') 
ml     <- list(ng = 1000, burnin = 200, typeNames = f$typeNames, holdoutN = 10)
output <- gjam(f$formula, f$xdata, f$ydata, modelList = ml)
ePCA   <- gjamOrdination(output, PLOT=TRUE)
eNMDS  <- gjamOrdination(output, PLOT=TRUE, method='NMDS')

## End(Not run)