Getting Started

In this section, we will take you through a short tutorial, to help you get acquainted with the main features of MTK. If you are already familiar with them, and are looking for detailed information on a specific plugin, we recommend you jump right to section , were we describe, individually, each of the available plugins. Our goal, here, will be to build a hidden Markov model to adequately represent a coin-tossing game, described below, and use it to forecast its future outcomes.

Suppose you are in a casino and, while walking through the main floor, you notice that there is a new strange game available, called Thank Paty the Parrot!. Curious, you walk up to the table, which has a green parrot standing on top of it, and ask the dealer about the game. Its rules are very simple. There are two coins inside a small basket, over the table, in front of the parrot. In each round, the parrot randomly chooses one, picking it up with his beak, and hands it over to the dealer. The dealer, then, flips the coin into the air. If it lands showing tails, you win $1$ dollar for every dollar bet, doubling your money. Otherwise, if it lands showing heads, the casino keeps all the money you bet. After the bets are payed, the dealer puts the coin back into the basket, shuffles it, and places it, again, in front of the parrot.

When asked about the coins, the dealer says that, despite being visually identical, they have different biases. One has a significant greater probability of showing heads, and the other has a significant probability of showing tails. So your chances of winning are conditioned on the parrots choice, thus the name Thank Paty the Parrot!. Paty, as you, can't tell the difference between both coins, but knows that every time he chooses one, he gets a nice pat on the head.

After hearing the explanation, you remember having read, just last week, a paper on hidden Markov models (HMM) [#!rabiner!#], and how they can be applied to situations just like the one described to you. Feeling that, finally, all that studying might pay off, you convince yourself that this is the game that's going to get you some money!

But before playing, you have to build your HMM model. To do this, you must first collect some observations, that will be used to estimate the parameters of the model. So you decide to observe others playing, and take notes on the outcomes of the coins. Your observations are recorded in the file trace.txt^11.1 in which a $1$ represents tails, and a $0$ represents heads. After collecting $1000$ observations^11.2, you head home and, using MTK, start building your HMM model.