corRLin {ramps}R Documentation

Linear Spatial Correlation Structure

Description

This function is a constructor for the 'corRLin' class, representing a linear spatial correlation structure. Letting r denote the range and n the nugget effect, the correlation between two observations a distance d < r apart is 1-(d/r) when no nugget effect is present and (1-n)*(1-(d/r)) when a nugget effect is assumed. If d >= r the correlation is zero.

Usage

   corRLin(value = numeric(0), form = ~ 1, nugget = FALSE,
           metric = c("euclidean", "maximum", "manhattan", "haversine"),
           radius = 3956, fixed = FALSE)

Arguments

value optional vector with the parameter values in constrained form. If nugget is FALSE, value can have only one element, corresponding to the “range” of the linear correlation structure, which must be greater than zero. If nugget is TRUE, meaning that a nugget effect is present, value can contain one or two elements, the first being the “range” and the second the “nugget effect” (one minus the correlation between two observations taken arbitrarily close together); the first must be greater than zero and the second must be between zero and one. Defaults to numeric(0), which results in a range of 90% of the minimum distance and a nugget effect of 0.1 being assigned to the parameters 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.
nugget optional logical value indicating whether a nugget effect is present. Defaults to FALSE. This argument exists for consistency with the nlme library and should be left set at its default value when used in georamps since the associated model includes a separate measurement error variance parameter.
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.
fixed optional logical value indicating whether the coefficients should be allowed to vary or be kept fixed at their initial value. This argument exists for consistency with the nlme library and is ignored in the ramps algorithm.

Value

Object of class 'corRLin', also inheriting from class 'corSpatial', representing a linear spatial correlation structure.

Note

When "haversine" is used as the distance metric, longitude and latitude coordinates must be given as the first and second covariates, respectively, in the formula specification for the form argument.

Author(s)

Brian Smith brian-j-smith@uiowa.edu and Jose Pinheiro Jose.Pinheiro@pharma.novartis.com, and Douglas Bates bates@stat.wisc.edu

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

corClasses, Initialize.corStruct, summary.corStruct

Examples

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

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

cs1Lin <- corRLin(1, form = ~ x + y)
cs1Lin <- Initialize(cs1Lin, spatDat)
corMatrix(cs1Lin)

cs2Lin <- corRLin(1, form = ~ x + y, metric = "man")
cs2Lin <- Initialize(cs2Lin, spatDat)
corMatrix(cs2Lin)

[Package ramps version 0.5-3 Index]