Modelling species abundance in a river by Negative Binomial hidden Markov models.

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	599-614
Journal	Computational Statistics and Data Analysis
Volume	71
Issue number	S1
Publication status	Published - 20 Jan 2014

Keywords

@article{2f91aa950db0444d8a7b2523b3f55da3,

title = "Modelling species abundance in a river by Negative Binomial hidden Markov models.",

keywords = "Bayesian inference, Board March 2014, Margaritifera, Markov chain, River Dee",

author = "L. Spezia and S.L. Cooksley and M.J. Brewer and D. Donnelly and A. Tree",

year = "2014",

month = jan,

day = "20",

language = "English",

volume = "71",

pages = "599--614",

journal = "Computational Statistics and Data Analysis",

number = "S1",

}

TY - JOUR

T1 - Modelling species abundance in a river by Negative Binomial hidden Markov models.

AU - Spezia, L.

AU - Cooksley, S.L.

AU - Brewer, M.J.

AU - Donnelly, D.

AU - Tree, A.

PY - 2014/1/20

Y1 - 2014/1/20

KW - Bayesian inference

KW - Board March 2014

KW - Margaritifera

KW - Markov chain

KW - River Dee

M3 - Article

VL - 71

SP - 599

EP - 614

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

IS - S1

ER -