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Integer-valued time series

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Integer-valued time series. / Fokianos, K.
In: Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 1, No. 3, 11.2009, p. 361-364.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Fokianos, K 2009, 'Integer-valued time series', Wiley Interdisciplinary Reviews: Computational Statistics, vol. 1, no. 3, pp. 361-364. https://doi.org/10.1002/wics.47

APA

Fokianos, K. (2009). Integer-valued time series. Wiley Interdisciplinary Reviews: Computational Statistics, 1(3), 361-364. https://doi.org/10.1002/wics.47

Vancouver

Fokianos K. Integer-valued time series. Wiley Interdisciplinary Reviews: Computational Statistics. 2009 Nov;1(3):361-364. doi: 10.1002/wics.47

Author

Fokianos, K. / Integer-valued time series. In: Wiley Interdisciplinary Reviews: Computational Statistics. 2009 ; Vol. 1, No. 3. pp. 361-364.

Bibtex

@article{5f0edcc47908492bbedf5ce3cad46b98,
title = "Integer-valued time series",
abstract = "Integer‐valued time series data appear in several diverse applications. However, modeling and inference for these types of dependent data pose several questions and interesting problems. The method of generalized linear models turns out to provide a sound framework for modeling and estimation whereby all computations are carried out by well‐established software. I review this area of research and propose some other models. ",
keywords = "generalized linear models , likelihood , prediction , stationarity",
author = "K. Fokianos",
year = "2009",
month = nov,
doi = "10.1002/wics.47",
language = "English",
volume = "1",
pages = "361--364",
journal = "Wiley Interdisciplinary Reviews: Computational Statistics",
number = "3",

}

RIS

TY - JOUR

T1 - Integer-valued time series

AU - Fokianos, K.

PY - 2009/11

Y1 - 2009/11

N2 - Integer‐valued time series data appear in several diverse applications. However, modeling and inference for these types of dependent data pose several questions and interesting problems. The method of generalized linear models turns out to provide a sound framework for modeling and estimation whereby all computations are carried out by well‐established software. I review this area of research and propose some other models.

AB - Integer‐valued time series data appear in several diverse applications. However, modeling and inference for these types of dependent data pose several questions and interesting problems. The method of generalized linear models turns out to provide a sound framework for modeling and estimation whereby all computations are carried out by well‐established software. I review this area of research and propose some other models.

KW - generalized linear models

KW - likelihood

KW - prediction

KW - stationarity

U2 - 10.1002/wics.47

DO - 10.1002/wics.47

M3 - Journal article

VL - 1

SP - 361

EP - 364

JO - Wiley Interdisciplinary Reviews: Computational Statistics

JF - Wiley Interdisciplinary Reviews: Computational Statistics

IS - 3

ER -