The article compares different methods for choosing the number of patterns in Hidden Markov models. It introduces new tests to check how well the models fit the data, and suggests a new way to pick the best number of patterns. The study looks at different types of data, like continuous, discrete, or zero-inflated. The tests were tried out in experiments to see how well they worked, and the results were compared with traditional methods.