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 journal › Article › Scientific › peer-review

Original language	English
Pages (from-to)	3-56
Number of pages	53
Journal	Journal of the Royal Statistical Society Series B-Statistical Methodology
Volume	62
Publication status	Published - 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-Statistical Methodology",

issn = "1369-7412",

publisher = "Oxford University Press",

}

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

SN - 1369-7412

VL - 62

SP - 3

EP - 56

JO - Journal of the Royal Statistical Society Series B-Statistical Methodology

JF - Journal of the Royal Statistical Society Series B-Statistical Methodology

ER -