This project implements a decoding algorithm using MCMC (Markov Chain Monte Carlo) methods in R. The approach leverages probabilistic sampling to estimate hidden states in a sequence, commonly used in applications like hidden Markov models and Bayesian inference. The code includes data preprocessing, model setup, and result.
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Updated
Sep 19, 2024 - R