Description Usage Arguments Value Examples
View source: R/convoSPAT_paramEst.R
This function generates another function to be used within optim
to
obtain maximum likelihood estimates of covariance (and possibly mean) parameters.
The function includes options for
(1) maximum likelihood ("ml"
) vs. restricted maximum likelihood
("reml"
),
(2) smoothness (kappa
): models without smoothness vs. estimating the
smoothness vs. using fixed smoothness,
(3) locally isotropic vs. locally anisotropic, and
(4) fixed nugget variance (tausq
): fixed vs. estimated.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
locations |
A matrix of locations. |
cov.model |
String; the covariance model. |
data |
A vector or matrix of data to use in the likelihood calculation. |
Xmat |
The design matrix for the mean model. |
nugg2.var |
Fixed values for the variance/covariance of the second nugget term; defaults to a matrix of zeros. |
tausq |
Scalar; fixed value for the nugget variance (when
|
kappa |
Scalar; fixed value for the smoothness (when |
fixed |
Logical vector of |
method |
Indicates the estimation method, either maximum likelihood ( |
local.aniso |
Logical; indicates if the local covariance should be
anisotropic ( |
fix.tausq |
Logical; indicates whether the default nugget term
(tau^2) should be fixed ( |
fix.kappa |
Logical; indicates if the kappa parameter should be
fixed ( |
This function returns another function for use in optim
.
1 2 3 4 | ## Not run:
make_local_lik( locations, cov.model, data, Xmat )
## End(Not run)
|
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