Hidden Markov Model Parameter Estimator
Hidden Markov Model Parameter Estimator estimates the parameters of an HMM with Gaussian emissions using the Baum-Welch algorithm. Enter observations as comma-separated values (e.g., “1.2,0.5,-0.3,1.8”), specify the number of hidden states, and the number of iterations. Results include the transition matrix \\( A \\), emission parameters (\\( \mu, \sigma^2 \\)), and initial probabilities \\( \pi \\), visualized with p5.js and steps shown in MathJax.
Hidden Markov Model Parameter Estimator
This calculator estimates the parameters of a Hidden Markov Model (HMM) with Gaussian emissions using the Baum-Welch algorithm. Input observations as comma-separated values (e.g., “1.2,0.5,-0.3,1.8”), the number of hidden states, and iterations. Outputs include the transition matrix \\( A \\), emission parameters (\\( \mu, \sigma^2 \\)), and initial probabilities \\( \pi \\). Results are visualized with p5.js, and computational steps are shown with MathJax.
Example 1: Two-State HMM
Observations: “1.2,0.5,-0.3,1.8”, States: 2, Iterations: 10.
Result: Transition matrix \\( A \\), means \\( \mu \\), variances \\( \sigma^2 \\), and initial probabilities \\( \pi \\).
Example 2: Three-State HMM
Observations: “0.1,0.4,2.3,2.8,0.2,0.5”, States: 3, Iterations: 20.
Result: Parameters for a three-state model.