Computes the log-likelihood for the spatio-temporal model.
uses an optimised version of the log-likelihood, while
uses the naive (slow) version and is included mainly for testing and speed
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Point at which to compute the log-likelihood, should be only
log-covariance parameters if
A single character indicating the type of log-likelihood to compute. Valid options are "f", "p", and "r", for full, profile or restricted maximum likelihood (REML).
Parameters to keep fixed,
Returns the log-likelihood of the spatio temporal model.
loglikeSTnaive may take long to run. However for
some problems with many locations and short time series
loglikeSTnaive could be faster than
Other likelihood functions:
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##load the data data(mesa.model) ##Compute dimensions for the data structure dim <- loglikeSTdim(mesa.model) ##Find out in which order parameters should be given loglikeST(NULL, mesa.model) ##Let's create random vectors of values x <- runif( dim$nparam.cov ) x.all <- runif( dim$nparam ) ##Evaluate the log-likelihood for these values loglikeST(x.all, mesa.model, "f") loglikeST(x, mesa.model, "p")
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