make.covar {sesem} | R Documentation |
Function to calculate covariance matrices for a set of lag distance bins
Description
calculates variance covariance matrices for each lag distance bin and for a flat (non-spatial) bin
Usage
make.covar(datafile,dist.mat,binsize,binname)
Arguments
datafile |
a dataset where the first two columns are x and y coordinates. Further columns contain observed variables for subsequent sesem modeling. |
dist.mat |
a vector containing distances between all X-Y sample pairs in a dataset. Produced by function calc.dist. |
binsize |
A vector of bin size cutoff distances starting with zero. Produced using make.bin |
binname |
A character vector of bin names. This vector has one element less than binsize. |
Details
Calculates variance-covariance matrices for a series of lag distance bins and for a flat (non-spatial) bin. This function produces a list object with four components: [[1]]bin.summary, [[2]] variable names [[3]] flat covariance matrix, [[4]][,,i] covariance matrices for each bin i. A summary of the bins is printed.
Value
1 |
A bin summary with colums binname, lower cutoff distance, upper cutoff distance, and sample size |
2 |
A list of observed variable names |
3 |
the flat (non-spatial) variance-covariance matrix |
4 |
contains elements [[4]][,,i] where each i is the variance - covariance matrix for a particular lag distance bin |
Author(s)
Kerrie Mengersen, Eric Lamb
References
Lamb, E. G., K. Mengersen, K. J. Stewart, U. Attanayake, and S. D. Siciliano. 2014. Spatially explicit structural equation modeling. Ecology 95:2434-2442.
See Also
make.bin
, make.covar
, runModels
Examples
data=truelove
truelove_red<-truelove[c(1:60),c(1:5)]
distancematrix<-calc.dist(truelove_red)
#calc.dist and make.covar can be time consuming to run,
# therefore only a small dataset utilized here
Truelove_bins<-make.bin(distancematrix,type="ALL",p.dist=5)
binsize<-Truelove_bins[1][[1]] #truelove lowland bin sizes
binname<-Truelove_bins[2][[1]] #truelove lowland bin names
covariances<-make.covar(truelove_red,distancematrix,binsize,binname)
covariances