Home > Research > Publications & Outputs > Estimation and testing linearity for non-linear...

Research

Associated organisational unit

Links

Text available via DOI:

View graph of relations

Estimation and testing linearity for non-linear mixed Poisson autoregressions

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

Published

Standard

Estimation and testing linearity for non-linear mixed Poisson autoregressions. / Christou, V.; Fokianos, K.
In: Electronic Journal of Statistics, Vol. 9, No. 1, 2015, p. 1357-1377.

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

Harvard

Christou, V & Fokianos, K 2015, 'Estimation and testing linearity for non-linear mixed Poisson autoregressions', Electronic Journal of Statistics, vol. 9, no. 1, pp. 1357-1377. https://doi.org/10.1214/15-EJS1044

APA

Christou, V., & Fokianos, K. (2015). Estimation and testing linearity for non-linear mixed Poisson autoregressions. Electronic Journal of Statistics, 9(1), 1357-1377. https://doi.org/10.1214/15-EJS1044

Vancouver

Christou V, Fokianos K. Estimation and testing linearity for non-linear mixed Poisson autoregressions. Electronic Journal of Statistics. 2015;9(1):1357-1377. doi: 10.1214/15-EJS1044

Author

Christou, V. ; Fokianos, K. / Estimation and testing linearity for non-linear mixed Poisson autoregressions. In: Electronic Journal of Statistics. 2015 ; Vol. 9, No. 1. pp. 1357-1377.

Bibtex

@article{83766381f76841418fc61887067a0798,
title = "Estimation and testing linearity for non-linear mixed Poisson autoregressions",
abstract = "Non-linear mixed Poisson autoregressive models are studied for the analysis of count time series. Given a correct mean specification of the model, we discuss quasi maximum likelihood estimation based on Poisson log-likelihood function. A score testing procedure for checking linearity of the mean process is developed. We consider the cases of identifiable and non identifiable parameters under the null hypothesis. When the parameters are identifiable then a chi-square approximation to the distribution of the score test is obtained. In the case of non identifiable parameters, a supremum score type test statistic is employed for checking linearity of the mean process. The methodology is applied to simulated and real data.",
author = "V. Christou and K. Fokianos",
year = "2015",
doi = "10.1214/15-EJS1044",
language = "English",
volume = "9",
pages = "1357--1377",
journal = "Electronic Journal of Statistics",
issn = "1935-7524",
publisher = "Institute of Mathematical Statistics",
number = "1",

}

RIS

TY - JOUR

T1 - Estimation and testing linearity for non-linear mixed Poisson autoregressions

AU - Christou, V.

AU - Fokianos, K.

PY - 2015

Y1 - 2015

N2 - Non-linear mixed Poisson autoregressive models are studied for the analysis of count time series. Given a correct mean specification of the model, we discuss quasi maximum likelihood estimation based on Poisson log-likelihood function. A score testing procedure for checking linearity of the mean process is developed. We consider the cases of identifiable and non identifiable parameters under the null hypothesis. When the parameters are identifiable then a chi-square approximation to the distribution of the score test is obtained. In the case of non identifiable parameters, a supremum score type test statistic is employed for checking linearity of the mean process. The methodology is applied to simulated and real data.

AB - Non-linear mixed Poisson autoregressive models are studied for the analysis of count time series. Given a correct mean specification of the model, we discuss quasi maximum likelihood estimation based on Poisson log-likelihood function. A score testing procedure for checking linearity of the mean process is developed. We consider the cases of identifiable and non identifiable parameters under the null hypothesis. When the parameters are identifiable then a chi-square approximation to the distribution of the score test is obtained. In the case of non identifiable parameters, a supremum score type test statistic is employed for checking linearity of the mean process. The methodology is applied to simulated and real data.

U2 - 10.1214/15-EJS1044

DO - 10.1214/15-EJS1044

M3 - Journal article

VL - 9

SP - 1357

EP - 1377

JO - Electronic Journal of Statistics

JF - Electronic Journal of Statistics

SN - 1935-7524

IS - 1

ER -