This is a tutorial that explains how you can match HMM inferred states with previously labelled states using the Hungarian algorithm.

In this activity we track the status of 500 individuals within a justice system.

Here, we review some stochastic dynamic programming problems in R.

In this series we look at a number of optimal allocation problems. We start with a basic problem related to the "Optimal Allocations In the Construction of k-out-of-n Reliability Systems” by Derman et al, 1974.

This is an R implementation of the gambling model with changing win probabilities from Chapter 1, section 4 (“A Gambling Model With Changing Win Probabilities”) of the “Introduction to Stochastic Dynamic Programming” book by Sheldon Ross.

This is an R implementation of the stock option model from Chapter 1, section 3 ("A Stock-Option Model") of the "Introduction to Stochastic Dynamic Programming" book by Sheldon Ross.

This is an R implementation of the gambling model from Chapter 1, section 2 ("A Gambling Model") of the "Introduction to Stochastic Dynamic Programming" book by Sheldon Ross.