logLik.frontier {frontier}

Extract Log-Likelihood Value

Description

Extract the log-likelihood value(s) from stochastic frontier models returned by frontier.

Usage

## S3 method for class 'frontier'
logLik( object, which = "mle", newParam = NULL, ... )

Arguments

object

an object of class frontier (returned by the function frontier).

which

character string. Which log-likelihood value should be returned? 'ols' for the log-likelihood value of the parameters estimated by OLS, 'grid' for the log-likelihood value of the parameters obtained by the grid search (only if no starting values were provided), 'start' for the log-likelihood value of the starting values of the parameters specified by the user (only if starting values were provided), or 'mle' for the log-likelihood values of the parameters estimated by Maximum Likelihood.

newParam

optional vector of parameters. If this argument is provided by the user, the log-likelihood value of the model object is calculated with these (new) parameters.

...

currently unused.

Value

logLik.frontier returns an object of class logLik, which is a numeric scalar (the log-likelihood value) with 2 attributes: nobs (total number of observations in all equations) and df (number of free parameters, i.e. length of the coefficient vector).

Author(s)

Arne Henningsen

See Also

frontier.

Examples

   # example included in FRONTIER 4.1
   data( front41Data )

   # SFA estimation with starting values obtained from a grid search
   sfaResult <- sfa( log( output ) ~ log( capital ) + log( labour ),
      data = front41Data )
   logLik( sfaResult, which = "ols" )
   logLik( sfaResult, which = "grid" )
   logLik( sfaResult )

   # SFA estimation with starting values provided by the user
   sfaResult2 <- sfa( log( output ) ~ log( capital ) + log( labour ),
      data = front41Data, startVal = 0.9 * coef( sfaResult ) )
   logLik( sfaResult2, which = "ols" )
   logLik( sfaResult2, which = "start" )
   logLik( sfaResult2 )

   # evaluate log likelihood function for a user-provided parameter vector
   logLik( sfaResult, newParam = 0.9 * coef( sfaResult ) )
      # equal to  logLik( sfaResult2, which = "start" )

   # log likelihood function for different values of gamma
   plot( t( sapply( seq( 0.05, 0.95, 0.05 ), function(x) c( x,
      logLik( sfaResult, newParam = c( coef( sfaResult )[1:4], x ) ) ) ) ) )