Evaluate spatial dependence model
evaluate
evaluates the spatial dependence model based on the provided arguments.
## S3 method for class 'cmodStd' evaluate(mod, d, e = TRUE, f = TRUE) evaluate(mod, d, e = TRUE, f = TRUE)
mod
: A covariance or semivariogram model.d
: An matrix of distances. If mod$ratio != 1
, i.e., if geometric anisotropy has been specified, then d
must be produced by the ganiso_d
function.e
: A single logical value indicating whether the error variance should be added to the returned covariance matrix. Default is TRUE
.f
: A single logical value indicating whether the finescale/microscale variance should be added to the returned covariance matrix. Default is TRUE
.Returns the evaluated model with necessary components needed for estimate
and predict
.
If mod
is of class cmodStd
(from the cmod_std
function), then the function returns an matrix with the evaluated standard covariance function.
n = 10 coords = matrix(runif(2*n), nrow = n, ncol = 2) d = as.matrix(dist(coords)) cmod = cmod_std(model = "exponential", psill = 1, r = 1) evaluate(cmod, d)
Joshua French
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