R: Optimizes the Composite indipendence log-likelihood

CompIndLik2 {GeoModels}

R Documentation

Optimizes the Composite indipendence log-likelihood

Description

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

Usage

CompIndLik2(bivariate, coordx, coordy ,coordt,
coordx_dyn, data, flagcorr, flagnuis, fixed,grid,
              lower, model, n, namescorr, namesnuis, 
              namesparam,
              numparam, optimizer, onlyvar, parallel, 
              param, spacetime, type,
              upper, namesupper, varest, ns, X,
              sensitivity,copula,MM)

Arguments

`bivariate`	Logical; if `TRUE` then the data come froma a bivariate random field. Otherwise from a univariate random field.
`coordx`	A numeric (`d \times 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.
`coordt`	A numeric vector assigning 1-dimension of temporal coordinates. Optional argument, the default is `NULL` then a spatial random field is expected.
`coordx_dyn`	A list of `m` numeric (`d_t \times 2`)-matrices containing dynamical (in time) spatial coordinates. Optional argument, the default is `NULL`
`data`	A numeric vector or a (`n \times d`)-matrix or (`d \times d \times n`)-matrix of observations.
`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 \times d`)-matrix, instead if `TRUE` then (`d \times d \times n`)-matrix is considered.
`lower`	An optional named list giving the values for the lower bound of the space parameter when the optimizer is `L-BFGS-B` or `nlminb` or `optimize`. The names of the list must be the same of the names in the `start` list.
`model`	Numeric; the id value of the density associated to the likelihood objects.
`n`	Numeric; number of trials in a binomial random fields.
`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.
`optimizer`	String; the optimization algorithm (see `optim` for details). `Nelder-Mead` is the default. Other possible choices are `nlm`, `BFGS` `L-BFGS-B` and `nlminb`. In these last two cases upper and lower bounds can be passed by the user. In the case of one-dimensional optimization, the function `optimize` is used.
`onlyvar`	Logical; if `TRUE` (and varest is `TRUE`) only the variance covariance matrix is computed without optimizing. `FALSE` is the default.
`parallel`	Logical; if `TRUE` optmization is performed using optimParallel using the maximum number of cores, when optimizer is `L-BFGS-B`.`FALSE` 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.
`type`	String; the type of the likelihood objects. If `Pairwise` (the default) then the marginal composite likelihood is formed by pairwise marginal likelihoods.
`upper`	An optional named list giving the values for the upper bound of the space parameter when the optimizer is or `L-BFGS-B` or `nlminb` or `optimize`. The names of the list must be the same of the names in the `start` list.
`namesupper`	String; the names of the upper limit of the parameters.
`varest`	Logical; if `TRUE` the estimate variances and standard errors are returned. `FALSE` is the default.
`ns`	Numeric; Number of (dynamical) temporal instants.
`X`	Numeric; Matrix of space-time covariates in the linear mean specification.
`sensitivity`	Logical; if `TRUE` then the sensitivy matrix is computed
`copula`	String; the type of copula. It can be "Clayton" or "Gaussian"
`MM`	Numeric;a non constant fixed mean

Value

Return a list from an optim call.

Author(s)