options ls=78;
title "Discriminant Analysis - Insect Data";

data insect;
  infile "D:\Statistics\STAT 505\data\insect.csv" firstobs=2 delimiter=',';
  input species $ joint1 joint2 aedeagus;
  run;

 /* A new data set called 'test' is created to store any new
  * values to be classified with our discriminant rule.
  * The variables must match the quantitative ones in the training set.
  */

data test;
  input joint1 joint2 aedeagus;
  cards;
  194 124 49
  ; run;

 /* The pool option conducts a test of equal covariance matrices.
  * If the results of the test are insignificant (at the 0.10 level), the
  * sample covariance matrices are pooled, resulting in a linear discriminant
  * function; otherwise, the sample covariance matrices are not pooled, 
  * resulting in a quadratic discriminant function.
  * The crossvalidate option calculates the confusion matrix based on 
  * the holdout method, where each obs is classified from the other obs only. 
  * The testdata= option specifies the data set with obs to be classified.
  * The testout= option specifies the name of the data set where classification
  * results are stored.
  * The class statement specifies the variable with groups for classification.
  * The var statement specifies the quantitative variables used to estimate
  * the mean and covariance matrices of the groups.
  */

proc discrim data=insect pool=test crossvalidate testdata=test testout=a;
  class species;
  var joint1 joint2 aedeagus;
  run;

 /* This will print the results of the classifications of the obs
  * from the 'test' data set.
  */

proc print data=a;
  run;