| coef | R Documentation |
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.
## S3 method for class 'sfacross'
coef(object, extraPar = FALSE, ...)
## S3 method for class 'summary.sfacross'
coef(object, ...)
## S3 method for class 'sfalcmcross'
coef(object, extraPar = FALSE, ...)
## S3 method for class 'summary.sfalcmcross'
coef(object, ...)
## S3 method for class 'sfaselectioncross'
coef(object, extraPar = FALSE, ...)
## S3 method for class 'summary.sfaselectioncross'
coef(object, ...)
object |
A stochastic frontier model returned by |
extraPar |
Logical (default =
|
... |
Currently ignored. |
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.
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.
## Not run:
## 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))
## End(Not run)
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