Copyright 2019 Andrew Garcia
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
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Simple Monte Carlo mc_simple.py: Sample inputs from their corresponding random distributions to generate output distribution.
Simulating Monte Hall problem through conditional selection (Monte Carlo algorithm)
The rejection sampling criterion:
U = [random number from uniform distribution (0,1)]
P(x) = Probability density function (e.g. ~ exp(-x**2))
if P(x) > U
accept x (label with blue)
else
reject x (label with orange)
can be understood to be based on the premise that sampling "U" values above those of a probability distribution of a certain event do not constitute a part of said event and are thus rejected.
Example: Marathon Race Outcomes under different strategies (run-jog-run/jog)
