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Amiri J, Farnoosh R, Behzadi M. A novel dependent NTA thinning operator and generalized geometric INAR(1) process with contagious disease case studies. COMMUN STAT-SIMUL C 2022. [DOI: 10.1080/03610918.2022.2087879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- J. Amiri
- Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - R. Farnoosh
- School of Mathematics, Iran University of Science and Technology, Tehran, Iran
| | - M.H. Behzadi
- Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, Iran
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Abstract
This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being entirely nonparametric and the second one being semiparametric computed under the corresponding null hypothesis. The asymptotic distribution of the proposed tests statistics both under the null hypotheses as well as under alternatives is derived and consistency is proved. The case of testing bivariate generalized Poisson autoregression and extension of the methods to dimension higher than two are also discussed. The finite-sample performance of a parametric bootstrap version of the tests is illustrated via a series of Monte Carlo experiments. The article concludes with applications on real data sets and discussion.
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Li C, Zhang H, Wang D. Modelling and monitoring of INAR(1) process with geometrically inflated Poisson innovations. J Appl Stat 2021; 49:1821-1847. [DOI: 10.1080/02664763.2021.1884206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Cong Li
- Center for Applied Statistical Research, School of Mathematics, Jilin University, Changchun, People's Republic of China
- Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, People's Republic of China
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, People's Republic of China
| | - Dehui Wang
- Center for Applied Statistical Research, School of Mathematics, Jilin University, Changchun, People's Republic of China
- School of Economics, Liaoning University, Shenyang, China
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Huang J, Zhu F. An alternative test for zero modification in the INAR(1) model with Poisson innovations. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2020.1869987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Jie Huang
- School of Mathematics, Jilin University, Changchun, China
| | - Fukang Zhu
- School of Mathematics, Jilin University, Changchun, China
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Time Series Regression for Zero-Inflated and Overdispersed Count Data: A Functional Response Model Approach. JOURNAL OF STATISTICAL THEORY AND PRACTICE 2020. [DOI: 10.1007/s42519-020-00094-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Some goodness-of-fit tests for the Poisson distribution with applications in Biodosimetry. Comput Stat Data Anal 2020. [DOI: 10.1016/j.csda.2019.106878] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Kang Y, Wang D, Yang K, Zhang Y. A new thinning-based INAR(1) process for underdispersed or overdispersed counts. J Korean Stat Soc 2020. [DOI: 10.1007/s42952-019-00010-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Möller TA, H. Weiß C, Kim HY, Sirchenko A. Modeling Zero Inflation in Count Data Time Series with Bounded Support. Methodol Comput Appl Probab 2017. [DOI: 10.1007/s11009-017-9577-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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