MTB > exec 'bayes_se'
MTB > ##################################################################
MTB > #  MACRO 'BAYES_SE'                                              #
MTB > # -------------------------------------------------------------- #
MTB > #  BAYES RULE FOR A FINITE NUMBER OF MODELS                      #
MTB > #  AND FINITE NUMBER OF OUTCOMES.                                #
MTB > #                                                                #
MTB > #  THIS PROGRAM SETS UP MODELS, PRIOR, AND LIKELIHOODS.          #
MTB > #                                                                #
MTB > #  THE MACRO 'BAYES' IMPLEMENTS BAYES RULE FOR A SEQUENCE        #
MTB > #  OF INDEPENDENT OUTCOMES.                                      #
MTB > ##################################################################
 
INPUT NUMBER OF MODELS:
DATA> 2
 
INPUT NAMES OF MODELS (ONE NAME ON EACH LINE):
DATA> have disease
DATA> don't have disease
 
INPUT PRIOR PROBABILITIES OF MODELS:
DATA> .001 .999
 
INPUT THE NUMBER OF POSSIBLE OUTCOMES:
DATA> 2
 
INPUT THE NAME OF EACH OBSERVATION:
 (ONE OBSERVATION ON A LINE)
DATA> +
DATA> -
 
INPUT LIKELIHOODS OF EACH MODEL:

MODEL   
   1 

DATA> .95 .05
      1 rows read.

MODEL   
   2 

DATA> .05 .95
      1 rows read.
 
OBSERVATION NAMES:

 Row            OBS  OBS_NAME

   1   OUT_1            +    
   2   OUT_2            -    

 
TABLE OF PROBABILITIES OF MODELS AND OUTCOMES:

 Row  MODEL           NAME   PRIOR  OUT_1  OUT_2

   1      1   have disease   0.001   0.95   0.05
   2      2   don't have d   0.999   0.05   0.95

MTB > exec 'bayes'
MTB > ##################################################################
MTB > #  MACRO 'BAYES'                                                 #
MTB > # -------------------------------------------------------------- #
MTB > #  IMPLEMENTS BAYES RULE FOR A SEQUENCE OF INDEPENDENT OUTCOMES. #
MTB > #  THE PROGRAM 'BAYES_SE' MUST BE RUN FIRST TO                   #
MTB > #  SET UP MODELS, PRIOR, AND LIKELIHOODS.                        #
MTB > ##################################################################
 
INPUT NUMBER OF OBSERVATIONS:
DATA> 1
 
INPUT OBSERVATIONS:
 (ONE OBSERVATION NAME ON A LINE:)
DATA> +

OUTCOME 
  +    

 Row  MODEL           NAME   PRIOR   LIKE   PRODUCT       POST

   1      1   have disease   0.001   0.95   0.00095   0.018664
   2      2   don't have d   0.999   0.05   0.04995   0.981336

SUMMARY OF PRIOR AND POSTERIOR MODEL PROBABILITIES:

 Row  OBS_NO  OUTCOMES     PROB_M1    PROB_M2

   1       0             0.0010000   0.999000
   2       1     +       0.0186640   0.981336