prais function

Extracting the regression of a twoStepsBenchmark

prais extracts the regression, which is an object of class "praislm", of a twoStepsBenchmark object.

prais(x)

praislm(X, y, include.rho, include.differenciation, set_coefficients, cl)

Arguments

• x: a twoStepsBenchmark

Returns

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 include.rho=FALSE

• 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)