summary method for class "prais".
# S3 method for prais
summary(object, ...)# S3 method for summary.prais
print(x, digits = max(3L, getOption("digits") -
3L), signif.stars = getOption("show.signif.stars"), ...)
an object of class "prais", usually, a result of a call to prais_winsten.
further arguments passed to or from other methods.
an object of class "summary.prais", usually, a result of a call to summary.prais.
the number of significant digits to use when printing.
logical. If TRUE, 'significance stars' are printed for each coefficient.
summary.prais returns a list of class "summary.prais", which contains the following components:
the matched call.
the residuals, that is the response minus the fitted values.
a named vector of coefficients.
the values of the AR(1) coefficient \(\rho\) from all iterations.
the square root of the estimated variance of the random error.
degrees of freedom, a 3-vector (p, n-p, p*), the first being the number of non-aliased coefficients, the last being the total number of coefficients.
R^2, the 'fraction of variance explained by the model', $$R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2),$$ where y* is the mean of y[i] if there is an intercept and zero otherwise.
the above R^2 statistic 'adjusted', penalising for higher p.
(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
a \(p x p\) matrix of (unscaled) covariances of the coef[j], j=1, ..., p.
a named 2-vector with the Durbin-Watson statistic of the original linear model and the Prais-Winsten estimator.
a character specifying the ID and time variables.