| residuals | R Documentation |
This function returns the residuals' values from stochastic frontier models
estimated with sfacross, sfalcmcross, or
sfaselectioncross.
## S3 method for class 'sfacross'
residuals(object, ...)
## S3 method for class 'sfalcmcross'
residuals(object, ...)
## S3 method for class 'sfaselectioncross'
residuals(object, ...)
object |
A stochastic frontier model returned
by |
... |
Currently ignored. |
When the object is of class 'sfacross', or
'sfaselectioncross', residuals returns a vector of
residuals values.
When the object is of 'sfalcmcross',
residuals returns a data frame containing the residuals values
for each latent class, where each variable ends with '_c#',
'#' being the class number.
The residuals values are ordered in the same way as the corresponding observations in the dataset used for the estimation.
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')
resid.tl_u_ts <- residuals(tl_u_ts)
head(resid.tl_u_ts)
## Using data on eighty-two countries production (GDP)
# LCM Cobb Douglas (production function) half normal distribution
cb_2c_h <- sfalcmcross(formula = ly ~ lk + ll + yr, udist = 'hnormal',
data = worldprod, S = 1)
resid.cb_2c_h <- residuals(cb_2c_h)
head(resid.cb_2c_h)
## End(Not run)
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