loglikeST: Compute the Log-likelihood for the Spatio-Temporal Model
In SpatioTemporal: Spatio-Temporal Model Estimation

Description Usage Arguments Value Warning Author(s) See Also Examples

Computes the log-likelihood for the spatio-temporal model. loglikeST uses an optimised version of the log-likelihood, while loglikeSTnaive uses the naive (slow) version and is included mainly for testing and speed checks.

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loglikeST(x = NULL, STmodel, type = "p", x.fixed = NULL)

loglikeSTnaive(x = NULL, STmodel, type = "p", x.fixed = NULL)

`x`	Point at which to compute the log-likelihood, should be only log-covariance parameters if `type=c("p","r")` and regression parameters followed by log-covariance parameters if `type="f"`. If `x=NULL` the function acts as an alias for `loglikeSTnames` returning the expected names of the input parameters.
`STmodel`	`STmodel` object with the model for which to compute the log-likelihood.
`type`	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).
`x.fixed`	Parameters to keep fixed, `NA` values in this vector is replaced by values from `x` and the result is used as `x`, ie. `x.fixed[ is.na(x.fixed) ] <- x` `x <- x.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 loglikeST.

Johan Lindstrom

Other STmodel functions: createCV, createDataMatrix, createSTmodel, dropObservations, estimateBetaFields, loglikeSTdim, predictNaive, processLUR, processLocation, updateCovf, updateTrend.STdata

Other likelihood functions: loglikeSTGrad

##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")