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A goodness-of-fit test for Poisson count processes

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A goodness-of-fit test for Poisson count processes. / Fokianos, K.; Neumann, M.H.
In: Electronic Journal of Statistics, Vol. 7, No. 1, 2013, p. 793-819.

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

Harvard

Fokianos, K & Neumann, MH 2013, 'A goodness-of-fit test for Poisson count processes', Electronic Journal of Statistics, vol. 7, no. 1, pp. 793-819. https://doi.org/10.1214/13-EJS790

APA

Fokianos, K., & Neumann, M. H. (2013). A goodness-of-fit test for Poisson count processes. Electronic Journal of Statistics, 7(1), 793-819. https://doi.org/10.1214/13-EJS790

Vancouver

Fokianos K, Neumann MH. A goodness-of-fit test for Poisson count processes. Electronic Journal of Statistics. 2013;7(1):793-819. doi: 10.1214/13-EJS790

Author

Fokianos, K. ; Neumann, M.H. / A goodness-of-fit test for Poisson count processes. In: Electronic Journal of Statistics. 2013 ; Vol. 7, No. 1. pp. 793-819.

Bibtex

@article{f1d8ffed9be246899a056ebd633d300d,
title = "A goodness-of-fit test for Poisson count processes",
abstract = "We are studying a novel class of goodness-of-fit tests for parametric count time series regression models. These test statistics are formed by considering smoothed versions of the empirical process of the Pearson residuals. Our construction yields test statistics which are consistent against Pitman{\textquoteright}s local alternatives and they converge weakly at the usual parametric rate. To approximate the asymptotic null distribution of the test statistics, we propose a parametric bootstrap method and we study its properties. The methodology is applied to simulated and real data.",
author = "K. Fokianos and M.H. Neumann",
year = "2013",
doi = "10.1214/13-EJS790",
language = "English",
volume = "7",
pages = "793--819",
journal = "Electronic Journal of Statistics",
issn = "1935-7524",
publisher = "Institute of Mathematical Statistics",
number = "1",

}

RIS

TY - JOUR

T1 - A goodness-of-fit test for Poisson count processes

AU - Fokianos, K.

AU - Neumann, M.H.

PY - 2013

Y1 - 2013

N2 - We are studying a novel class of goodness-of-fit tests for parametric count time series regression models. These test statistics are formed by considering smoothed versions of the empirical process of the Pearson residuals. Our construction yields test statistics which are consistent against Pitman’s local alternatives and they converge weakly at the usual parametric rate. To approximate the asymptotic null distribution of the test statistics, we propose a parametric bootstrap method and we study its properties. The methodology is applied to simulated and real data.

AB - We are studying a novel class of goodness-of-fit tests for parametric count time series regression models. These test statistics are formed by considering smoothed versions of the empirical process of the Pearson residuals. Our construction yields test statistics which are consistent against Pitman’s local alternatives and they converge weakly at the usual parametric rate. To approximate the asymptotic null distribution of the test statistics, we propose a parametric bootstrap method and we study its properties. The methodology is applied to simulated and real data.

U2 - 10.1214/13-EJS790

DO - 10.1214/13-EJS790

M3 - Journal article

VL - 7

SP - 793

EP - 819

JO - Electronic Journal of Statistics

JF - Electronic Journal of Statistics

SN - 1935-7524

IS - 1

ER -