Computational Efficiency and Precision for Replicated-Count and Batch-Marked Hidden Population Models.

ABSTRACT: We address two computational issues common to open-population N-mixture models, hidden integer-valued autoregressive models, and some hidden Markov models. The first issue is computation time, which can be dramatically improved through the use of a fast Fourier transform. The second issue is tractability of the model likelihood function for large numbers of hidden states, which can be solved by improving numerical stability of calculations. As an illustrative example, we detail the application of these methods to the open-population N-mixture models. We compare computational efficiency and precision between these methods and standard methods employed by state-of-the-art ecological software. We show faster computing times (a ∼6 to ∼30 times speed improvement for population siz

SUBMITTER: Parker MRP 

PROVIDER: S-EPMC9434542 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature