poisplot Poissonness plot for discrete distributions poisplot

Visualizing Categorical Data: poisplot

$Version: 1.4 (31 Aug 2006)
Michael Friendly
York University

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

Poissonness plot for discrete distributions

The POISPLOT macro constructs a ``Poissonness plot'' for determining if discrete data follows the Poisson distribution. The plot has a linear relation between the count metameter n(k) and the basic count, k, when the distribution is Poisson. An influence plot displays the effect of each observed frequency on the choice of the Poisson parameter, lambda.



The POISPLOT macro is called with keyword parameters. The COUNT= and FREQ= parameters are required. The arguments may be listed within parentheses in any order, separated by commas. For example:
  %poisplot(count=Deaths,freq=corpsyrs, plot=dist);


Default values are shown after the name of each parameter.
The name of the input data set [Default: DATA=_LAST_]
The name of the basic count variable
The name of the variable giving the number of occurrences of COUNT.
Label for the horizontal (COUNT=) variable. If not specified the variable label for the COUNT= variable in the input data set is used.
Trial value of the Poisson parameter lambda to level the plot. If LAMBDA=0 (the default) the plot is not levelled.
Multiplier for error bars [Default: Z=1.96]
What to plot: DIST and/or INFL [Default: PLOT=DIST INFL]
Height of text labels [Default: HTEXT=1.4]
The name of the output data set [Default: OUT=POISPLOT]
Name of the graphics catalog entry [Default: NAME=POISPLT]


%include vcd(poisplot);        *-- or include in an autocall library;
  data horskick;
     input deaths corpsyrs;
     label deaths='Number of Deaths'
        corpsyrs='Number of Corps-Years';
        0    109
        1     65
        2     22
        3      3
        4      1
  %poisplot(count=Deaths,freq=corpsyrs, plot=dist);

See also

distplot Plots for discrete distributions
goodfit Goodness of fit tests for discrete distributions
ordplot Diagnose form of discrete frequency distribution
rootgram Hanging rootograms for discrete distributions

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