/* 

  Chi dist (generating samples) in Picat.

  From Handbook on probability distributions
  page 77ff

  See ppl_distributions.pi for the definitions of PDF, CDF, and quantile, and
  ppl_distributions_test.pi for tests of these.

  Cf my Gamble model gamble_chi_dist.rkt

  This program was created by Hakan Kjellerstrand, hakank@gmail.com
  See also my Picat page: http://www.hakank.org/picat/

*/

import ppl_distributions, ppl_utils.
import util.
% import ordset.

main => go.

/*

  var : g
  Probabilities (truncated):
  4.87092964949741: 0.0001000000000000
  4.253810460859521: 0.0001000000000000
  4.067932844874163: 0.0001000000000000
  4.020446960939659: 0.0001000000000000
  .........
  0.020199275520739: 0.0001000000000000
  0.018373645714474: 0.0001000000000000
  0.008625360767505: 0.0001000000000000
  0.002433029924934: 0.0001000000000000
  mean = 1.24948

  var : mean theoretical
  Probabilities:
  1.25331: 1.0000000000000000
  mean = 1.25331

*/
go ?=>
  reset_store,
  run_model(10_000,$model,[show_probs_trunc,mean]),
  nl,
  % show_store_lengths,nl,
  % fail,
  nl.
go => true.
  
  
model() =>
  K = 2,
  G = chi_dist(K),

  Mean = chi_dist_mean(K),
  
  add("g",G),
  add("mean theoretical",Mean).