gradients.sfaFLW: Returning Gradients

In npFrontier: Non-Parametric and Semi-Parametric Stochastic Frontier Analysis

Description

This method returns the gradients of the dependent variable with respect to the explanatory variables obtained from semiparametric stochastic frontier models estimated with function sfaFLW.

Usage

## S3 method for class 'sfaFLW'
gradients( x, ... )

Arguments

x	a semiparametric stochastic frontier model estimated with function sfaFLW.
...	currently ignored.

Value

A numeric matrix containing the gradients obtained in the nonparametric regression (first step). Each row corresponds to one observation and each column corresponds to one explanatory variable.

Author(s)

Arne Henningsen

See Also

sfaFLW, gradients, fitted.sfaFLW.

Examples

  # example included in FRONTIER 4.1 (cross-section data)
  data( front41Data, package = "frontier" )

  # semiparametric local-constant Cobb-Douglas production frontier
  FLW_Result <- sfaFLW( log( output ) ~ log( capital ) + log( labour ),
    data = front41Data )
    
  # fitted values of the nonparametric regression (first step)
  fitted( FLW_Result, which = "first" )

  # bias-corrected fitted values of the frontier function
  fitted( FLW_Result )

npFrontier documentation built on May 2, 2019, 4:48 p.m.