Sequential Poisson Regression in Diffusion Networks

0524262 - ÚTIA 2021 RIV US eng J - Článek v odborném periodiku
Dedecius, Kamil - Žemlička, R.
Sequential Poisson Regression in Diffusion Networks.
IEEE Signal Processing Letters. Roč. 27, č. 1 (2020), s. 625-629. ISSN 1070-9908. E-ISSN 1558-2361
Institucionální podpora: RVO:67985556
Klíčová slova: diffusion * distributed estimation * Poisson regression
Obor OECD: Electrical and electronic engineering
Impakt faktor: 3.109, rok: 2020
Způsob publikování: Omezený přístup
http://library.utia.cas.cz/separaty/2020/AS/dedecius-0524262.pdf https://ieeexplore.ieee.org/document/9066870

The Poisson regression is a popular model for positive integer random variables determined by known explanatory variables. This letter studies the problem of its collaborative Bayesian sequential estimation under potentially slowly time-varying regression coefficients. We assume networks where agents share their information about the inferred quantities with adjacent neighbors in order to improve the overall estimation performance. The communication strategy is the information diffusion, i.e., only one information exchange per time instant is allowed.
Trvalý link: http://hdl.handle.net/11104/0308918