hmm

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§Hidden Markov Model

§Example

Lets say that we have 2 coins:

  • Fair which generates H (Head) and T (Tails) with probability of 1/2
  • Biased - with probabilities H: 1/4, T: 3/4

We also know that after each toss we can switch coin with the probability of

  • Use the same coin: 3/4
  • Switch coin: 1/4

First time we select coin with probability of 1/2

Question: If we now get observation of H H T T T which coins were used during each toss?

Lest build HMM model for this example and check the answer:

let initials: Vec<f64> = vec![0.5, 0.5];
let st = vec![0.75, 0.25, 0.25, 0.75];
let obs = vec![0.5, 0.5, 0.25, 0.75];
let hmm = HiddenMarkov::from_vec(initials, st, obs).unwrap();
hmm.map_estimate(vec![0, 0, 1, 1, 1]) == vec![0, 0, 1, 1, 1]

Structs§

  • HiddenMarkov
    Specialized structure for Hidden Markov Model of order 1 The states are identified by ids taken from natural numbers.