geoBayes (version 0.5.1)

likaprxn: Log-likelihood approximation

Description

Log-likelihood approximation

Usage

likaprxn(linkp, phi, omg, kappa, formula, family = "gaussian", data, weights,
  subset, atsample, corrfcn = "matern", np, betm0, betQ0, ssqdf, ssqsc, tsqdf,
  tsqsc, dispersion = 1, longlat = FALSE)

Arguments

linkp

Parameter of the link function. For binomial, a positive number for the degrees of freedom of the robit family or "logit" or "probit". For the other families any number for the exponent of the Box-Cox transformation. Input can be a scalar or a vector.

phi

Spatial range parameter. Input can be a scalar or a vector.

omg

Relative nugget parameter. Input can be a scalar or a vector.

kappa

Spatial smoothness parameter. Input can be a scalar or a vector.

formula

A representation of the model in the form response ~ terms.

family

The distribution of the response. Can be one of the options in .geoBayes_models or "transformed.gaussian".

data

An optional data frame containing the variables in the model.

weights

An optional vector of weights. Number of replicated samples for Gaussian and gamma, number of trials for binomial, time length for Poisson.

subset

An optional vector specifying a subset of observations to be used in the fitting process.

atsample

A formula in the form ~ x1 + x2 + ... + xd with the coordinates of the sampled locations.

corrfcn

Spatial correlation function. Can be one of the choices in .geoBayes_corrfcn.

np

The number of integration points for the spatial variance parameter sigma^2. The total number of points will be 2*np + 1.

betm0

Prior mean for beta (a vector or scalar).

betQ0

Prior standardised precision (inverse variance) matrix. Can be a scalar, vector or matrix. The first two imply a diagonal with those elements. Set this to 0 to indicate a flat improper prior.

ssqdf

Degrees of freedom for the scaled inverse chi-square prior for the partial sill parameter.

ssqsc

Scale for the scaled inverse chi-square prior for the partial sill parameter.

tsqdf

Degrees of freedom for the scaled inverse chi-square prior for the measurement error parameter.

tsqsc

Scale for the scaled inverse chi-square prior for the measurement error parameter.

dispersion

The fixed dispersion parameter.

longlat

How to compute the distance between locations. If FALSE, Euclidean distance, if TRUE Great Circle distance. See spDists.

Value

A vector of the same length as the parameters containing the log-likelihood values.

Details

Computes and approximation to the log-likelihood for the given parameters.