distplot Plots for discrete distributions distplot

Visualizing Categorical Data: distplot

$Version: 1.3 (10 Jan 2001)
Michael Friendly
York University

The distplot macro ( [download] get distplot.sas)

Plots for discrete distributions

The DISTPLOT macro constructs plots of a discrete distribution designed to diagnose whether the data follows one of the standard distributions: the Poisson, Binomial, Negative Binomial, Geometric, or Log Series, specified by the DIST= parameter. The usual (PLOT=DIST) plot is constructed so that the points lie along a straight line when the data follows that distribution. An influence plot (PLOT=INFL) shows the influence of each observation on the choice of the distribution parameter(s).

Usage

The DISTPLOT macro is called with keyword parameters. You must specify the distribution to be fit (DIST=). and the COUNT= and FREQ= variables. The arguments may be listed within parentheses in any order, separated by commas. For example: 

  %distplot(data=queues, count=women, freq=queues, dist=binomial,
      parm=0.435);

Parameters

DATA=
The name of the input data set [Default: DATA=_LAST_]
COUNT=
Basic count variable
FREQ=
Number of occurrences of count
LABEL=
Horizontal (count) label
DIST=
Name of distribution, one of POISSON, BINOMIAL, GEOMETRIC, or LOGSERIES,
PARM=
Trial value of the distribution parameter(s) to level the plot. For the Binomial distribution, PARM=p, the binomial probability of success; for the Poisson, PARM=lambda, the Poisson mean
Z=
Multiplier for error bars in the PLOT=DIST plot. [Default: Z=1.96]
PLOT=
What to plot: DIST and/or INFL [Default: PLOT=DIST]
HTEXT=
Height of text labels in the plots [Default: HTEXT=1.4]
OUT=
The name of the output data set [Default: OUT=DISTPLOT]
NAME=
Name of the graphics catalog entry [Default: NAME=DISTPLT]

Example

%include vcd(distplot);        *-- or include in an autocall library;

%distplot();

See also

goodfit Goodness of fit tests for discrete distributions
ordplot Diagnose form of discrete frequency distribution
poisplot Poissonness plot for discrete distributions
rootgram Hanging rootograms for discrete distributions