data.prep: data.prep objects

In skiptoniam/bbgdm: Bayesian Bootstrap Generalised Dissimilarity Models.

Description

prepares table of occurrence records or precence-absence matrix for use in bbgdm.

Usage

table2pam(x, site.id = "site.id", sp.id = "sp.id", abund = FALSE,
  abund.col = " No.of.specimens", siteXsp = TRUE)

pam2dissim(y, dism_metric = "number_non_shared")

simulate_covariates(y, n)

Arguments

x	data to be imported into R. A table of species occurrences and site records.
site.id	Name of column that contains site names /IDs.
sp.id	Name of column that contains species information/ID.
abund	LOGICAL if TRUE calculate abundances.
abund.col	Name of column that contains abundance/counts data.
siteXsp	LOGICAL if TRUE Returns sites as rows, sites as columns, if FALSE returns species as rows and sites as cols.
y	presence-absence matrix of site x sp.
dism_metric	If "bray_curtis" calculates Bray-Curtis dissimilarity, if "number_non_shared " returns number of shared species at site_ij which can be used in a binomial model for GDM.
n	number of covariates to simulate

Value

A species by sites matrix for use in dissimilarity calculation

dism a vector of dissimilarities or count of shared species calcualted for the upper-triangle of a dissimilarity matrix.

Examples

x <- matrix(rbinom(16,1,.6),4,4) #toy presence absence matrix
covr <- simulate_covariates(x,6)

skiptoniam/bbgdm documentation built on May 30, 2019, 1:05 a.m.