CompLikelihood: Optimizes the Composite log-likelihood
In CompRandFld: Composite-Likelihood Based Analysis of Random Fields

Description Usage Arguments Author(s) See Also

Subroutine called by FitComposite. The procedure estimates the model parameters by maximisation of the composite log-likelihood.

CompLikelihood(coordx, coordy, corrmodel, data, distance, 
               flagcorr, flagnuis, fixed, grid, likelihood, 
               lower, model, namescorr, namesnuis, namesparam,
               numparam, numparamcorr, optimizer, param,
               spacetime, threshold, type, upper, varest,
               vartype, winconst, winstp)

`coordx`	A numeric (d x 2)-matrix (where `d` is the number of points) assigning 2-dimensions of coordinates or a numeric vector assigning 1-dimension of coordinates.
`coordy`	A numeric vector assigning 1-dimension of coordinates; `coordy` is interpreted only if `coordx` is a numeric vector otherwise it will be ignored.
`corrmodel`	Numeric; the id of the correlation model.
`data`	A numeric vector or a (n x d)-matrix or (d x d x n)-matrix of observations.
`distance`	String; the name of the spatial distance. The default is `Eucl`, the euclidean distance. See the Section Details.
`flagcorr`	A numeric vector of binary values denoting which paramerters of the correlation function will be estimated.
`flagnuis`	A numeric vector of binary values denoting which nuisance paramerters will be estimated.
`fixed`	A numeric vector of parameters that will be considered as known values.
`grid`	Logical; if `FALSE` (the default) the data are interpreted as a vector or a (n x d)-matrix, instead if `TRUE` then (d x d x n)-matrix is considered.
`likelihood`	String; the configuration of the compositelikelihood, see `FitComposite`.
`lower`	A numeric vector with the lower bounds of the parameters' ranges.
`model`	Numeric; the id value of the density associated to the likelihood objects.
`namescorr`	String; the names of the correlation parameters.
`namesnuis`	String; the names of the nuisance parameters.
`namesparam`	String; the names of the parameters to be maximised.
`numparam`	Numeric; the number of parameters to be maximised.
`numparamcorr`	Numeric; the number of correlation parameters.
`optimizer`	String; the optimization algorithm (see `optim` for details). 'Nelder-Mead' is the default.
`param`	A numeric vector of parameters' values.
`spacetime`	Logical; if `TRUE` the random field is spatial-temporal otherwise is a spatial field.
`threshold`	Numeric; a value indicating a threshold for the binary random field, see `FitComposite`.
`type`	String; the type of the likelihood objects. If `Pairwise` (the default) then the marginal composite likelihood is formed by pairwise marginal likelihoods.
`upper`	A numeric vector with the upper bounds of the parameters' ranges.
`varest`	Logical; if `TRUE` the estimate' variances and standard errors are returned. `FALSE` is the default.
`vartype`	String; the type of estimation method for computing the estimate variances, see `FitComposite`.
`winconst`	Numeric; a positive value – if `vartype=SubSamp` – determines the window size in the sub-sampling estimates of the variances, see `FitComposite`.
`winstp`	Numeric; a positive value – if `vartype=SubSamp` – determines the window step in the sub-sampling estimates of the variances, see `FitComposite`.