deform (version 1.0.0)

aniso: Fitting anisotropic spatial Gaussian process models

Description

Function aniso fits a conventional 2-dimensional anisotropic Gaussian process, i.e. just with scalings in the x and y coordinates.

Usage

aniso(x, z, n, correlation = FALSE, cosine = FALSE, standardise = "together")

Value

An object of class deform and then of class anisotropic

Arguments

x

a 2-column matrix comprising x and y coordinates column-wise, respectively, or a list; see Details for the latter

z

a variance-covariance matrix

n

an integer number of data

correlation

a logical defining whether z should be assumed to be a correlation matrix; defaults to FALSE

cosine

a logical defining whether the powered exponential covariance function should be multiplied by the cosine of scaled distances, i.e. giving a damped oscillation; defaults to FALSE

standardise

a character string that governs whether dimensions are scaled by a common ("together") or dimension-specific factor; defaults to "together"

Details

If x is a list, then it wants elements "x", "z" and "n" as described above.

References

Sampson, P. D. and Guttorp, P. (1992) Nonparametric Estimation of Nonstationary Spatial Covariance Structure, Journal of the American Statistical Association, 87:417, 108-119, tools:::Rd_expr_doi("10.1080/01621459.1992.10475181")'

Examples

data(solar)
aniso(solar$x, solar$z, solar$n) 
# equivalent to aniso(solar)