In this paper, we introduce a new integer valued bilinear modeling based on the Pegram and thinning operators. Some statistical properties of the model are discussed. The model parameters are estimated by the conditional least square and Yule-Walker methods. By a simulation, the performances of the two estimation methods are studied. Finally, the efficiency of the proposed model is investigated by applying it on two real data sets.
Mohammadpour, M., & Ramezani, S. (2020). An integer-valued bilinear time series model via random Pegram and thinning operators. Journal of Advanced Mathematical Modeling, 10(1), 215-230. doi: 10.22055/jamm.2020.28321.1679
MLA
Mehrnaz Mohammadpour; Sakineh Ramezani. "An integer-valued bilinear time series model via random Pegram and thinning operators". Journal of Advanced Mathematical Modeling, 10, 1, 2020, 215-230. doi: 10.22055/jamm.2020.28321.1679
HARVARD
Mohammadpour, M., Ramezani, S. (2020). 'An integer-valued bilinear time series model via random Pegram and thinning operators', Journal of Advanced Mathematical Modeling, 10(1), pp. 215-230. doi: 10.22055/jamm.2020.28321.1679
VANCOUVER
Mohammadpour, M., Ramezani, S. An integer-valued bilinear time series model via random Pegram and thinning operators. Journal of Advanced Mathematical Modeling, 2020; 10(1): 215-230. doi: 10.22055/jamm.2020.28321.1679
)