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

Research output: Contribution to Journal › Article › Academic

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
DOIs	https://doi.org/10.1111/1467-9868.00218
Publication status	Published - 2000

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@article{07804ff904aa44d5bff542c932f4edaf,

title = "Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives",

author = "S.J. Koopman and J. Durbin",

year = "2000",

doi = "10.1111/1467-9868.00218",

language = "English",

volume = "62",

pages = "3--56",

journal = "Journal of the Royal Statistical Society. Series B. Statistical Methodology",

issn = "1369-7412",

publisher = "Wiley-Blackwell",

}

TY - JOUR

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

AU - Koopman, S.J.

AU - Durbin, J.

PY - 2000

Y1 - 2000

U2 - 10.1111/1467-9868.00218

DO - 10.1111/1467-9868.00218

M3 - Article

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

SN - 1369-7412

ER -