macro

d_bayes mdl prr data;
 nlik k;
 store post;
 plot.

mcolumn mdl prr data MODEL PRIOR LIKE POSTR post nlike
mcolumn col PRODUCT
mconstant k11 k12 k13 k MEAN

let PRIOR=prr
let MODEL=mdl

%like model data like;
num k.

let prior=abs(prior)/sum(abs(prior))
let product=prior*like
let postr=product/sum(product)

if plot=1
layout
# title 'Prior, Likelihood, and Posterior';
# tsize 2.

let nlike=like/sum(like)
let k11=max(prior)
let k12=max(nlike)
let k13=max(postr)
set  col
 k11 k12 k13
end
let k11=max(col)

plot PRIOR*MODEL;
minimum 2 0;
maximum 2 k11;
project;
 size 3;
data;
 etype 0;
axis 1;
 tsize 2;
axis 2;
 label '';
tick 1;
 tsize 1.5;
tick 2;
 tsize 1.5;
figure 0 .5 .5 .9;
 etype 0;
title 'PRIOR';
 size 2.

plot NLIKE*MODEL;
minimum 2 0;
maximum 2 k11;
project;
size 3;
data;
etype 0;
axis 1;
 tsize 2;
axis 2;
 label '';
tick 1;
 tsize 1.5;
tick 2;
 tsize 1.5;
figure .5 1 .5 .9;
etype 0;
title 'LIKELIHOOD';
size 2.

plot POSTR*MODEL;
minimum 2 0;
maximum 2 k11;
project;
size 3;
data;
etype 0;
axis 1;
 tsize 2;
axis 2;
 label '';
tick 1;
 tsize 1.5;
tick 2;
 tsize 1.5;
figure .25 .75 .05 .45;
etype 0;
title 'POSTERIOR';
size 2.
gpause

endlayout

endif

notitle
mtitle 'PRIOR AND POSTERIOR DENSITIES OF MODELS:'
print MODEL PRIOR LIKE PRODUCT POSTR
let mean=sum(MODEL*PRIOR)
mtitle 'PRIOR MEAN OF MODELS:'
prin mean
let mean=sum(MODEL*POSTR)
mtitle 'POSTERIOR MEAN OF MODELS:'
prin mean
note

let POST=POSTR

endmacro