Document Type : Research Paper
Department of Statistics, Iran Banking Institute, Central Bank of Iran, Tehran, Iran.
There are many different fields the change point analysis arises. In those cases, the main problem is locating the unknown change points. The aim of this study is to detect location and time of change point in Poisson regression model. We assume for years before and after the change point , then observation has a Poisson distribution with parameters , respectively. We used several methods for estimation change point in real mortality data by assume Poisson regression model. Using two simulated and real data analysis showed that the change point has been occurred in year 1993 and this confirmed by all methods. Our findings have shown that the change pattern of mortality trend in Iran is related to improvement of health indicators and decreasing mortality rate in Iran.
- Assareh, H., Noorossana, R., & Mengersen, K. L. (2013). Bayesian change point estimation in Poisson-based control charts. Journal of industrial engineering international, 9(1), 1-13.
- Benson, A., & Friel, N. (2018). Adaptive MCMC for multiple change point analysis with applications to large datasets. Electronic journal of statistics, 12(2), 3365-3396.
- Chen, J., & Gupta, A. K. (2014). Parametric statistical change point analysis: With applications to genetics, medicine, and finance. Birkhauser Boston. https://doi.org/10.1007/978-0-8176-4801-5
- Chernoyarov, O. V., Kutoyants, Y. A., & Top, A. (2018). On multiple change-point estimation for Poisson process. Communications in statistics-theory and methods, 47(5), 1215-1233.
- Jarrett, R. G. (1979). A note on the intervals between coal-mining disasters. Biometrika, 66(1), 191-193.
- Khosravi, A., Taylor, R., Naghavi, M., & Lopez, A. D. (2007). Mortality in the Islamic republic of Iran, 1964-2004. Bulletin of the world health organization, 85, 607-614.
- Mohammad, I. (2006). Trends and patterns of mortality in china, Japan and India: a comparative analysis. The social sciences, 1(3), 149-153.
- Ng, K. H., Midi, H., & Ng, K. H. (2017). Change point detection of robust individuals control chart. International journal of industrial engineering: theory, applications, and practice, 24(5). https://doi.org/10.23055/ijietap.2017.24.5.2947
- Nyambura, S., Mundai, S., & Waititu, A. (2016). Estimation of change point in Poisson random variables using the maximum likelihood method. American journal of theoretical and applied statistics, 5(4), 219-224.
- Pina-Monarrez, M. R. (2018). Generalization of the Hotelling's decomposition method to the r- chart. International journal of industrial engineering: theory, applications and practice, 25(2). https://doi.org/10.23055/ijietap.2018.25.2.2053
- Shaochuan, L. (2019). A Bayesian multiple change point model for marked Poisson processes with applications to deep earthquakes. Stochastic environmental research and risk assessment, 33(1), 59-72.