Time series analysis of Non-Gaussian observations based on state space models from both classical and Bayesian perspectives

J. Durbin, S.J.M. Koopman

Research output: Contribution to journalArticleScientificpeer-review

Original languageEnglish
Pages (from-to)3-56
Number of pages53
JournalJournal of the Royal Statistical Society, Series B
Volume62
Publication statusPublished - 2000

Cite this

@article{aeb4ed8128bf4505aaf71aa13cc2122b,
title = "Time series analysis of Non-Gaussian observations based on state space models from both classical and Bayesian perspectives",
author = "J. Durbin and S.J.M. Koopman",
note = "DP 98142 Pagination: 53",
year = "2000",
language = "English",
volume = "62",
pages = "3--56",
journal = "Journal of the Royal Statistical Society, Series B",
issn = "1369-7412",
publisher = "Wiley-Blackwell",

}

Time series analysis of Non-Gaussian observations based on state space models from both classical and Bayesian perspectives. / Durbin, J.; Koopman, S.J.M.

In: Journal of the Royal Statistical Society, Series B, Vol. 62, 2000, p. 3-56.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Time series analysis of Non-Gaussian observations based on state space models from both classical and Bayesian perspectives

AU - Durbin, J.

AU - Koopman, S.J.M.

N1 - DP 98142 Pagination: 53

PY - 2000

Y1 - 2000

M3 - Article

VL - 62

SP - 3

EP - 56

JO - Journal of the Royal Statistical Society, Series B

JF - Journal of the Royal Statistical Society, Series B

SN - 1369-7412

ER -