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help for rdplot
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Plot residual distribution after model fit

        rdplot [plottype] [, residualtype rscale(exp) by(varname)
                 [at(numlist) | group(#)] graph_options plot(plot) ]


Description

    rdplot is for use after regress and similar commands; see help on the
    command of interest.

    rdplot graphs residual distributions. The residuals are, by default,
    those calculated by predict, residuals or (if the previous estimation
    command was glm) by predict, response.

    The graph by default is a single or multiple dotplot, as produced by
    dotplot.

    Histograms or box plots may be selected by specifying either histogram or
    hbox or box as plottype.

    Oneway plots as implemented by onewayplot, skewness plots as implemented
    by skewplot, or quantile plots as implemented by qplot may be selected by
    specifying onewayplot or skewplot or qplot as plottype.

        In the latter three cases, onewayplot or skewplot or qplot must be
        installed first.  In the last case, qplot plottypes may be specified
        in full (e.g. as qplot line); by default qplot or an abbreviation of
        it means qplot connected.

    plottype may be abbreviated unambiguously, i.e. down as far as d, hi, hb,
    b, o or s or q.


Options

    residualtype specifies a type of residual other than the default.  The
        following types are currently supported: anscombe, deviance,
        likelihood, pearson, residuals, response, rstandard, rstudent, score,
        working.

    rscale(exp) specifies a transformed scale on which to show the residuals
        using Stata syntax and X as a placeholder for the residual variable
        name. Thus rscale(X^2) specifies squaring, to show relative
        contribution to residual variance; rscale(abs(X)) specifies absolute
        value, to set aside sign; rscale(sqrt(abs(X))) specifies root of
        absolute value, a useful scale on which to check for
        heteroscedasticity.

    by(varname) specifies that plots should be given for groups of varname.
        If at() or group() is also specified, as below, groups are as
        specified by that option. Otherwise, groups are the distinct values
        of varname.

    at(numlist) or group(#) specifies how groups of a classifying variable
        are to be determined.  If by(varname) is specified, as above, at() or
        group() is applied to that variable. Otherwise, the first-named
        predictor or covariate used in the previous regression-type command
        is used. at() and group() are options of egen, cut(): see help on 
        egen. In brief, at() specifies lower limits of user-defined classes
        and group() specifies the number of quantile-based groups with
        (approximately) equal frequency to be used. (With at(), supply one
        high value beyond the maximum of the data for best results.)

    graph_options are any of the options allowed with whichever of dotplot,
        histogram, graph hbox, graph box, onewayplot or skewplot is selected
        as plottype.

    plot(plot) provides a way to add other plots to the generated graph; see 
        plot_option. plot() is allowed whenever plottype permits (and so not
        with dotplot, box or hbox).


Examples

    . reg width length
    . rdplot, g(3)
    . foreach v in width length {
    .         gen log`v' = log(`v')
    . }
    . reg logwidth loglength
    . rdplot, g(3)
    . rdplot b, g(3)
    . rdplot hb, g(3)
    . rdplot hi, g(3)

    . glm price weight, link(log)
    . rdplot hi, anscombe yli(0) normal


Author

    Nicholas J. Cox, University of Durham, U.K.
        n.j.cox@durham.ac.uk


Also see