gjamSpec2Trait: Ecological traits for gjam analysis
In dbystrova/GJAM_clust: Generalized Joint Attribute Modeling

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

Constructs community-weighted mean-mode (CWMM) trait matrix for analysis with gjam for n observations, S species, P traits, and M total trait levels.

1	gjamSpec2Trait(pbys, sbyt, tTypes)

`pbys`	`n x S` plot by species matrix (presence-absence, abundance)
`sbyt`	`S x P` species by trait matrix
`tTypes`	`P` data types for trait columns

Generates the objects needed for a trait response model (TRM). As inputs the sbyt data.frame has P columns containing numeric values, ordinal scores, and categorical variables, identified by data type in tTypes. Additional trait columns can appear in the n x M output matrix plotByCWMM, because each level of a category becomes a new 'FC' column as a CWMM. Thus, M can exceed P, depending on the number of factors in sbyt. The exception is for categorical traits with only two levels, which can be treated as (0, 1) censored 'CA' data.

As output, the CWMM data types are given in traitTypes.

The list censor = NULL unless some data types are censored. In the example below there are two censored columns.

A detailed vignette on trait analysis is obtained with:

browseVignettes('gjam')

`plotByCWM`	`n x M matrix` of community-weight means (numeric) or modes (ordinal)
`traitTypes`	`character vector` of data types for traits
`specByTrait`	`S x M matrix` translates species to traits
`censor`	`list` of censored columns, values, and intervals; see `gjamCensorY`

James S Clark, jimclark@duke.edu

Clark, J.S. 2016. Why species tell us more about traits than traits tell us about species: Predictive models. Ecology 97, 1979-1993.

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, gjamCensorY

## Not run: 
library(repmis)
source_data("https://github.com/jimclarkatduke/gjam/blob/master/forestTraits.RData?raw=True")

xdata       <- forestTraits$xdata
plotByTree  <- gjamReZero(forestTraits$treesDeZero) # re-zero
traitTypes  <- forestTraits$traitTypes
specByTrait <- forestTraits$specByTrait

tmp <- gjamSpec2Trait(pbys = plotByTree, sbyt = specByTrait, 
                      tTypes = traitTypes)
tTypes <- tmp$traitTypes
traity <- tmp$plotByCWM
censor <- tmp$censor

ml  <- list(ng=2000, burnin=500, typeNames = tTypes, censor = censor)
out <- gjam(~ temp + stdage + deficit, xdata, ydata = traity, modelList = ml)
pl  <- list(SMALLPLOTS=F)           
gjamPlot(output = out, plotPars = pl)         

## End(Not run)