loglik.GRF(geodata, coords = geodata$coords, data = geodata$data,
cov.model = "exp", cov.pars, nugget = 0, kappa = 0.5,
lambda = 1, psiR = 1, psiA = 0,
trend = "cte", method.lik = "ML", compute.dists = TRUE,
realisations = NULL)
coords
and
data
as described next.
Typically an object of the class "geodata"
- a geoR
data-set.
If not provided the arguments
coords
and data
coords
of the argument geodata
.data
of the argument geodata
.cov.spatial
."cte"
(constant mean),
"1st"
(a first degree polynomial
on the coordinates), "2nd"
(a second degree polynomial
on the coordinates), or a form"ML"
for likelihood and "REML"
for
restricted likelihood. Defaults to "ML"
.as.geodata
.The expression restricted log-likelihood is: $$rl(\theta) = -\frac{n-p}{2} \log (2\pi) + \frac{1}{2} \log |F' F| - \frac{1}{2} \log |\Sigma| - \frac{1}{2} \log |F' \Sigma F| - \frac{1}{2} (y - F\beta)' \Sigma^{-1} (y - F\beta).$$
likfit
for likelihood-based parameter estimation.if(is.R()) data(s100)
loglik.GRF(s100, cov.pars=c(0.8, .25), nugget=0.2)
loglik.GRF(s100, cov.pars=c(0.8, .25), nugget=0.2, met="RML")
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