

   RReeggrreessssiioonn DDiiaaggnnoossttiiccss

        lm.influence(lm.obj)

   AArrgguummeennttss::

     lm.obj: an object as returned by `lm'.

   DDeessccrriippttiioonn::

        This function provides the basic quantities which are
        used in forming a wide variety of diagnostics for
        checking the quality of regression fits.

        The functions listed below give a more direct way of
        computing a variety of regression diagnostics.

   VVaalluuee::

        A list containing the following components:

        hat: a vector containing the diagonal of the ``hat''
             matrix.

   coefficients: the change in the estimated coefficients which
             results when the i-th case is dropped from the
             regression is contained in the i-th row of this
             matrix.

      sigma: a vector whose i-th element contains the estimate
             of the residual standard deviation obtained when
             the i-th case is dropped from the regression.

   NNoottee::

        The `coefficients' returned by the R version of
        `lm.influence' differ from those computed by S.  Rather
        than returning the coefficients which result from drop-
        ping each case, we return the changes in the coeffi-
        cients.  This is more directly useful in many diagnos-
        tic measures.

   RReeffeerreenncceess::

        Belsley, D. A., E. Kuh and R. E. Welsch (1980).
        Regression Diagnostics.  New York: Wiley.

   SSeeee AAllssoo::

        `summary.lm' for `summary' and related methods; `influ-
        ence.measures', `hat' for the hat matrix diagonals,
        `dfbetas', `dffits', `covratio', `cooks.distance',
        `lm'.

   EExxaammpplleess::

        # Analysis of the life-cycle savings data
        # given in Belsley, Kuh and Welsch.
        data(savings)
        summary(lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data=savings),corr= TRUE)
        rstudent(lm.SR)
        dfbetas(lm.SR)
        dffits(lm.SR)
        covratio(lm.SR)

