This function is a constructor for the corSpatial class,
representing a spatial correlation structure. This class is "virtual",
having four "real" classes, corresponding to specific spatial
correlation structures, associated with it: corExp,
corGaus, corLin, corRatio, and
corSpher. The returned object will inherit from one of these
"real" classes, determined by the type argument, and from the
"virtual" corSpatial class. Objects created using this
constructor must later be initialized using the appropriate
Initialize method.
corSpatial(value, form, nugget, type, metric, fixed)an object of class determined by the type argument and also
inheriting from class corSpatial, representing a spatial
correlation structure.
an 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
spatial 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.
a one sided formula of the form ~ S1+...+Sp, or
~ S1+...+Sp | g, specifying spatial covariates S1
through Sp and, optionally, a grouping factor g.
When a grouping factor is present in form, the correlation
structure is assumed to apply only to observations within the same
grouping level; observations with different grouping levels are
assumed to be uncorrelated. Defaults to ~ 1, which corresponds
to using the order of the observations in the data as a covariate,
and no groups.
an optional logical value indicating whether a nugget
effect is present. Defaults to FALSE.
an optional character string specifying the desired type of
correlation structure. Available types include "spherical",
"exponential", "gaussian", "linear", and
"rational". See the documentation on the functions
corSpher, corExp, corGaus, corLin, and
corRatio for a description of these correlation
structures. Partial matching of arguments is used, so only the first
character needs to be provided.Defaults to "spherical".
an 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; and "manhattan"
for the sum of the absolute differences. Partial matching of
arguments is used, so only the first three characters need to be
provided. Defaults to "euclidean".
an optional logical value indicating whether the
coefficients should be allowed to vary in the optimization, or kept
fixed at their initial value. Defaults to FALSE, in which case
the coefficients are allowed to vary.
José Pinheiro and Douglas Bates bates@stat.wisc.edu
Cressie, N.A.C. (1993), "Statistics for Spatial Data", J. Wiley & Sons.
Venables, W.N. and Ripley, B.D. (2002) "Modern Applied Statistics with S", 4th Edition, Springer-Verlag.
Littel, Milliken, Stroup, and Wolfinger (1996) "SAS Systems for Mixed Models", SAS Institute.
corExp,
corGaus,
corLin,
corRatio,
corSpher,
Initialize.corStruct,
summary.corStruct,
dist
sp1 <- corSpatial(form = ~ x + y + z, type = "g", metric = "man")
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