State sequence estimation

State sequence estimation is a process used to determine the best series of hidden states or conditions that lead to a series of observed events, particularly in fields like statistics or machine learning. Imagine you're trying to figure out the weather conditions over a week based on daily temperature readings. The true weather conditions (like sunny or rainy) are often hidden, but you can estimate them by analyzing the observed temperatures. This estimation helps in predicting future states based on past data, improving decision-making in various applications, from finance to robotics.