sfaR (version 1.0.0)

coef: Extract coefficients of stochastic frontier models

Description

From an object of class 'summary.sfacross', 'summary.sfalcmcross', or 'summary.sfaselectioncross', coef extracts the coefficients, their standard errors, z-values, and (asymptotic) P-values.

From on object of class 'sfacross', 'sfalcmcross', or 'sfaselectioncross', it extracts only the estimated coefficients.

Usage

# S3 method for sfacross
coef(object, extraPar = FALSE, ...)
# S3 method for summary.sfacross
coef(object, ...)
# S3 method for sfalcmcross
coef(object, extraPar = FALSE, ...)
# S3 method for summary.sfalcmcross
coef(object, ...)
# S3 method for sfaselectioncross
coef(object, extraPar = FALSE, ...)
# S3 method for summary.sfaselectioncross
coef(object, ...)

Value

For objects of class 'summary.sfacross', 'summary.sfalcmcross', or 'summary.sfaselectioncross', coef returns a matrix with four columns. Namely, the estimated coefficients, their standard errors, z-values, and (asymptotic) P-values.

For objects of class 'sfacross', 'sfalcmcross', or 'sfaselectioncross', coef returns a numeric vector of the estimated coefficients. If extraPar = TRUE, additional parameters, detailed in the section ‘Arguments’, are also returned. In the case of object of class 'sfalcmcross', each additional parameter ends with '#' that represents the class number.

Arguments

object

A stochastic frontier model returned by sfacross, sfalcmcross, or sfaselectioncross, or an object of class 'summary.sfacross', 'summary.sfalcmcross', or
'summary.sfaselectioncross'.

extraPar

Logical (default = FALSE). If TRUE, additional parameters are returned:

sigmaSq = sigmauSq + sigmavSq

lambdaSq = sigmauSq/sigmavSq

sigmauSq = \(\exp{(Wu)}\) = \(\exp{(\bm{\delta}' \mathbf{Z}_u)}\)

sigmavSq = \(\exp{(Wv)}\) = \(\exp{(\bm{\phi}' \mathbf{Z}_v)}\)

sigma = sigmaSq^0.5

lambda = lambdaSq^0.5

sigmau = sigmauSq^0.5

sigmav = sigmavSq^0.5

gamma = sigmauSq/(sigmauSq + sigmavSq)

...

Currently ignored.

See Also

sfacross, for the stochastic frontier analysis model fitting function using cross-sectional or pooled data.

sfalcmcross, for the latent class stochastic frontier analysis model fitting function using cross-sectional or pooled data.

sfaselectioncross for sample selection in stochastic frontier model fitting function using cross-sectional or pooled data.

Examples

if (FALSE) {
## Using data on fossil fuel fired steam electric power generation plants in the U.S.
# Translog SFA (cost function) truncated normal with scaling property
tl_u_ts <- sfacross(formula = log(tc/wf) ~ log(y) + I(1/2 * (log(y))^2) +
log(wl/wf) + log(wk/wf) + I(1/2 * (log(wl/wf))^2) + I(1/2 * (log(wk/wf))^2) +
I(log(wl/wf) * log(wk/wf)) + I(log(y) * log(wl/wf)) + I(log(y) * log(wk/wf)),
udist = 'tnormal', muhet = ~ regu, uhet = ~ regu, data = utility, S = -1,
scaling = TRUE, method = 'mla')
coef(tl_u_ts, extraPar = TRUE)
coef(summary(tl_u_ts))
}