prais {disaggR} | R Documentation |
Extracting the regression of a twoStepsBenchmark
Description
prais extracts the regression, which is an object of class "praislm"
, of a
twoStepsBenchmark object.
Usage
prais(x)
praislm(X, y, include.rho, include.differenciation, set_coefficients, cl)
Arguments
x |
a twoStepsBenchmark |
Value
prais returns an object of class "praislm"
.
The functions that can be used on that class are almost the same than
for the class twoStepsBenchmark
.
summary
, coefficients
, residuals
will return the same values.
However, as for fitted.values
, the accessor returns the fitted values
of the regression, not the high-frequency, eventually integrated, time series
contained in a twoStepsBenchmark.
An object of class "praislm"
is a list containing the following components :
coefficients |
a named vector of coefficients. |
residuals |
the residuals, that is response minus fitted values. |
fitted.values |
a time series, the fitted mean values |
se |
a named vector of standard errors. |
df.residuals |
the residual degrees of freedom. |
rho |
the autocorrelation coefficients of the residuals. It
is equal to zero if twoStepsBenchmark was called with |
residuals.decorrelated |
the residuals of the model after having been transformed by rho in a least square model. |
fitted.values.decorrelated |
the fitted values of the model after having been transformed by rho in a least square model. |
Examples
benchmark <- twoStepsBenchmark(turnover,construction); prais(benchmark)