Comment on "Under-reported data analysis with INAR-hidden Markov chains"
Abstract
In Fernandez-Fontelo et al (Statis. Med. 2016, DOI 10.1002/sim.7026) hidden integer-valued autoregressive (INAR) processes are used to estimate reporting probabilities for various diseases. In this comment it is demonstrated that the Poisson INAR(1) model with time-homogeneous underreporting can be expressed equivalently as a completely observed INAR(inf) model with a geometric lag structure. This implies that estimated reporting probabilities depend on the assumed lag structure of the latent process.
Keywords
Cite
@article{arxiv.1812.06688,
title = {Comment on "Under-reported data analysis with INAR-hidden Markov chains"},
author = {Johannes Bracher},
journal= {arXiv preprint arXiv:1812.06688},
year = {2019}
}
Comments
This is the pre-reviewing version of a letter published in Statistics in Medicine 38(5), 893-898: https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8032 Fernandez-Fontelo et al published a reply which raises some interesting further points: https://onlinelibrary.wiley.com/doi/10.1002/sim.8033 After a 12 month embargo period the accepted version will be made available on arxiv