ramps (version 0.6.18)

corRExpwr: Powered Exponential Spatial Correlation Structure

Description

This function is a constructor for the 'corRExpwr' class, representing a powered exponential spatial correlation structure. Letting \(r\) denote the range and \(p\) the shape, the correlation between two observations a distance \(d\) apart is \(\exp(-(d/r)^p)\).

Usage

corRExpwr(value = numeric(0), form = ~ 1,
             metric = c("euclidean", "maximum", "manhattan", "haversine"),
             radius = 3956)

Value

Object of class 'corRExpwr', also inheriting from class 'corRSpatial', representing a powered exponential spatial correlation structure.

Arguments

value

optional numeric vector of two parameter values for the powered exponential correlation structure, corresponding to the “range” and “shape”. The range parameter value must be greater than zero, and the shape in the interval (0, 2]. Defaults to numeric(0), which results in a range of 90% of the minimum distance and a shape of 1 being assigned to the parameter when object is initialized.

form

one-sided formula of the form ~ S1+...+Sp, specifying spatial covariates S1 through Sp. Defaults to ~ 1, which corresponds to using the order of the observations in the data as a covariate.

metric

optional character string specifying the distance metric to be used. The currently available options are "euclidean" for the root sum-of-squares of distances; "maximum" for the maximum difference; "manhattan" for the sum of the absolute differences; and "haversine" for the great-circle distance (miles) between longitude/latitude coordinates. Partial matching of arguments is used, so only the first three characters need to be provided. Defaults to "euclidean".

radius

radius to be used in the haversine formula for great-circle distance. Defaults to the Earth's radius of 3,956 miles.

Author

Brian Smith

References

Cressie, N.A.C. (1993), “Statistics for Spatial Data”, J. Wiley & Sons.

Venables, W.N. and Ripley, B.D. (1997) “Modern Applied Statistics with S-plus”, 2nd Edition, Springer-Verlag.

See Also

corRClasses

Examples

sp1 <- corRExpwr(form = ~ x + y + z)

spatDat <- data.frame(x = (0:4)/4, y = (0:4)/4)

cs1Expwr <- corRExpwr(c(1, 1), form = ~ x + y)
cs1Expwr <- Initialize(cs1Expwr, spatDat)
corMatrix(cs1Expwr)

cs2Expwr <- corRExpwr(c(1, 1), form = ~ x + y, metric = "man")
cs2Expwr <- Initialize(cs2Expwr, spatDat)
corMatrix(cs2Expwr)