Returns the indices of the variables used in fitting the model.
Returns the OLS (ordinary least squares) estimates of the regression coefficients. Entries beyond the intercept correspond to entries in basis.
Returns estimated standard errors of coefficients. Entries beyond the intercept correspond to entries in basis.
Computes Cook's distances.
Returns the number of degrees of freedom in the model.
Prints the least squares regression summary. Variables not used in the fit are marked as aliased.
Returns the fitted values for the model.
With no argument, NIL means a case is not used in calculating estimates, and non-nil means it is used. NEW-INCLUDED is a sequence of length of y of nil and t to select cases. Estimates are recomputed.
With no argument returns T if the model includes an intercept term, nil if not. With an argument NEW-INTERCEPT the model is changed to include or exclude an intercept, according to the value of NEW-INTERCEPT.
Returns the diagonal elements of the hat matrix.
Returns the number of cases in the model.
Returns the number of coefficients in the fit model (including the intercept if the model includes one).
Returns the number of cases used in the computations.
Opens a window with a plot of the standardized residuals and two standard error bars for the posterior distribution of the actual deviations from the line. See Chaloner and Brant. If X-VALUES are not supplied the fitted values are used. The plot can be linked to other plots with the link-views function. Returns a plot object.
Opens a window with a plot of the residuals. If X-VALUES are not supplied the fitted values are used. The plot can be linked to other plots with the link-views function. Returns a plot object.
With no argument returns the predictor names. NAMES sets the names.
Returns the sample squared multiple correlation coefficient, R squared, for the regression.
Returns the raw residuals for a model.
Returns the raw residuals for a model without weights. If the model includes weights the raw residuals times the square roots of the weights are returned.
Returns the estimated standard deviation of the deviations about the regression line.
Computes the internally studentized residuals for included cases and externally studentized residuals for excluded cases.
Returns the error sum of squares for the model.
With no argument returns the weight sequence as supplied to m; NIL means an unweighted model. NEW-W sets the weights sequence to NEW-W and recomputes the estimates.
Returns the X matrix for the model, including a column of 1's, if appropriate. Columns of X matrix correspond to entries in basis.
Returns or .