summary | R Documentation |
Create and print summary results for stochastic frontier models returned by
sfacross
, sfalcmcross
, or
sfaselectioncross
.
## S3 method for class 'sfacross'
summary(object, grad = FALSE, ci = FALSE, ...)
## S3 method for class 'summary.sfacross'
print(x, digits = max(3, getOption("digits") - 2), ...)
## S3 method for class 'sfalcmcross'
summary(object, grad = FALSE, ci = FALSE, ...)
## S3 method for class 'summary.sfalcmcross'
print(x, digits = max(3, getOption("digits") - 2), ...)
## S3 method for class 'sfaselectioncross'
summary(object, grad = FALSE, ci = FALSE, ...)
## S3 method for class 'summary.sfaselectioncross'
print(x, digits = max(3, getOption("digits") - 2), ...)
object |
An object of either class |
grad |
Logical. Default = |
ci |
Logical. Default = |
... |
Currently ignored. |
x |
An object of either class |
digits |
Numeric. Number of digits displayed in values. |
The summary
method returns a list of class
'summary.sfacross'
, 'summary.sfalcmcross'
, or
'summary.sfaselectioncross'
that contains the same elements as an object returned by sfacross
,
sfalcmcross
, or sfaselectioncross
with the
following additional elements:
AIC |
Akaike information criterion. |
BIC |
Bayesian information criterion. |
HQIC |
Hannan-Quinn information criterion. |
sigmavSq |
For |
sigmauSq |
For |
Varu |
For |
theta |
For |
Eu |
For |
Expu |
For |
olsRes |
For |
ols2StepRes |
For |
mlRes |
Matrix of ML estimates, their standard errors, z-values,
asymptotic P-values, and when |
chisq |
For |
df |
Degree of freedom for the inefficiency model. |
sfacross
, for the stochastic frontier analysis model
fitting function for cross-sectional or pooled data.
sfalcmcross
, for the latent class stochastic frontier analysis
model fitting function for cross-sectional or pooled data.
sfaselectioncross
for sample selection in stochastic frontier
model fitting function for cross-sectional or pooled data.
print
for printing sfacross
object.
coef
for extracting coefficients of the
estimation.
efficiencies
for computing
(in-)efficiency estimates.
fitted
for extracting the fitted frontier
values.
ic
for extracting information criteria.
logLik
for extracting log-likelihood
value(s) of the estimation.
marginal
for computing marginal effects of
inefficiency drivers.
residuals
for extracting residuals of the
estimation.
vcov
for computing the variance-covariance
matrix of the coefficients.
bread
for bread for sandwich estimator.
estfun
for gradient extraction for each
observation.
skewnessTest
for implementing skewness test.
## 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')
summary(tl_u_ts, grad = TRUE, ci = TRUE)
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