Theoretical Distance Based Covariance Functions
DESCRIPTION:
Computes theoretical covariance function at supplied distance values.
Models include exponential, spherical, and gaussian covariances.
USAGE:
exp.cov(distance, range, sill=1, nugget=0, eps=1.0e-7)
spher.cov(distance, range, sill=1, nugget=0, eps=1.0e-7)
gauss.cov(distance, range, sill=1, nugget=0, eps=1.0e-7)
REQUIRED ARGUMENTS:
- distance
-
a vector of distances to compute the covariance for.
- range
-
the range value.
OPTIONAL ARGUMENTS:
- sill
-
the sill value.
This is the absolute sill, the variance (covariance at
distance = 0
)
is
sill
+
nugget
.
- nugget
-
the nugget effect.
- eps
-
any distance less than
eps
will be set to
nugget + sill
.
VALUE:
a vector of covariance values at the supplied distances.
DETAILS:
These functions are used with the
krige
function.
SEE ALSO:
,
EXAMPLES:
dist <- seq(0,5,length=50)
plot(dist,exp.cov(dist,range=2,nugget=.2),type='l')