evaluate: Evaluate spatial dependence model

In gear: Geostatistical Analysis in R

Description

evaluate evaluates the spatial dependence model based on the provided arguments.

Usage

## S3 method for class 'cmodStd'
evaluate(mod, d, e = TRUE, f = TRUE)

evaluate(mod, d, e = TRUE, f = TRUE)

Arguments

mod	A covariance or semivariogram model.
d	An n \times m 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.

Details

If mod is of class cmodStd (from the cmod_std function), then the function returns an n \times m matrix with the evaluated standard covariance function.

Value

Returns the evaluated model with necessary components needed for estimate and predict.

Author(s)

Joshua French

Examples

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)

gear documentation built on April 14, 2020, 5:12 p.m.