Estimate Covariance Parameters

Used to estimate spatial covariance parameters for a few different spatial models, including the Exponential, Gaussian, and Spherical. Estimated parameters can then be used in predict to predict unobserved values.

estcovparm(response, designmatrix, xcoordsvec, ycoordsvec,
  CorModel = "Exponential", estmethod = "REML", covestimates = c(NA,
  NA, NA), pivec = NA, Vnn = NA)

Arguments

response	a vector of a response variable, possibly with missing values.
designmatrix	is the matrix of covariates used to regress the response on.
xcoordsvec	is a vector of x coordinates
ycoordsvec	is a vector of y coordinates
CorModel	is the covariance structure. By default, covstruct is
estmethod	is either the default "REML" for restricted maximum likelihood to estimate the covariance parameters and regression coefficients or "ML" to estimate the covariance parameters and regression coefficients. Exponential but other options include the Spherical and the Gaussian.
covestimates	is an optional vector of covariance parameter estimates (nugget, partial sill, range). If these are given and estmethod = "None", the the provided vector are treated as the estimators to create the covariance structure.
pivec	is a vector of estimated detection probabilities on each of the sites
Vnn	is the covariance matrix for the estimated detection probabilities

Value

a list with

• a vector of estimated covariance parameters

• the estimated covariance matrix for all sites

• the QR decomposition

• a vector of estimated fixed effects

• other components used in slmfit

Details

The function is used internally in slmfit.