2017-10-15 18:48:32 +00:00
|
|
|
|
|
|
|
|
#### Simulation of a Markov chain walk in a binary tree
|
|
|
|
|
|
|
|
|
|
File *mcBinTree.py* runs several simulations and takes the mean of
|
|
|
|
|
each experiment and outputs the plot of the mean and the stopping
|
|
|
|
|
time of the simulation.
|
|
|
|
|
|
|
|
|
|
File *oneRunMC.py* is just a single experiment of the simulation.
|
|
|
|
|
|
|
|
|
|
File *mcSim.py* shows how fast in Total Variation norm does the
|
|
|
|
|
Markov Chain converges to the stationary distribution.
|
|
|
|
|
|
|
|
|
|
File *makeTree.py* build a special tree data structure.
|
|
|
|
|
|
|
|
|
|
File *mcMatrix.py* builds a matrix from a tree created by *makeTree.py*.
|
|
|
|
|
|
|
|
|
|
File *totalVariationNorm.py* has two of the ways to measure the TV
|
|
|
|
|
norm.
|
|
|
|
|
|
|
|
|
|
**Note:** the n-arity of the tree can be changed, but the code might
|
|
|
|
|
have to be changed a bit.
|
|
|
|
|
|
