SFM.CI: Confidence Intervals for Estimates by MLE

In clemenshaerder/fepsfrontieR: Estimation of fixed-effect panel stochastic frontier models by MLE

Description

Computes two-sided Confidence Intervals for the regression coefficients based on the Hessian Matrix if they are computed by MLE. The variance is asymptotically chi-squared distributed and the regression coefficients asymptotically normal.

Usage

SFM.CI(estimates, hessianMatrix, alpha, N, Time, df)

Arguments

estimates	is a vector of regression coefficients & variance parameters. 1st parameter: sigma_u, 2nd parameter: sigma_v, followed by K beta & R delta coefficients.
hessianMatrix	is the Hessian Matrix of the MLE.
alpha	is a vector of significance levels.
N	is an integer (n - panels)
Time	is an integer (observations per panel)
df	are the degrees of freedom

Value

A matrix is returned with the confidence interval and the standard erros for each estimate as a data frame.

clemenshaerder/fepsfrontieR documentation built on May 22, 2019, 3:43 p.m.