Necessary and Sufficient Conditions for Stochastic Convergence of the Kernel Estimation of the Intensity Function of Non-Homogeneous Poisson Process in R²
The intensity function of the non-homogeneous Poisson process, that is defined on R² will be estimated by using kernel method, and it will be searched for necessary and sufficient conditions to have a uniform convergence in probability, almost sure, and almost completely sure.
Elsayigh, A., Amira, T., & Kalantan, Z. (2002). Necessary and Sufficient Conditions for Stochastic Convergence of the Kernel Estimation of the Intensity Function of Non-Homogeneous Poisson Process in R². The Egyptian Statistical Journal, 46(2), 167-191. doi: 10.21608/esju.2002.313797
MLA
Anga M. Elsayigh; Tarek A. Amira; Zakia E. Kalantan. "Necessary and Sufficient Conditions for Stochastic Convergence of the Kernel Estimation of the Intensity Function of Non-Homogeneous Poisson Process in R²", The Egyptian Statistical Journal, 46, 2, 2002, 167-191. doi: 10.21608/esju.2002.313797
HARVARD
Elsayigh, A., Amira, T., Kalantan, Z. (2002). 'Necessary and Sufficient Conditions for Stochastic Convergence of the Kernel Estimation of the Intensity Function of Non-Homogeneous Poisson Process in R²', The Egyptian Statistical Journal, 46(2), pp. 167-191. doi: 10.21608/esju.2002.313797
VANCOUVER
Elsayigh, A., Amira, T., Kalantan, Z. Necessary and Sufficient Conditions for Stochastic Convergence of the Kernel Estimation of the Intensity Function of Non-Homogeneous Poisson Process in R². The Egyptian Statistical Journal, 2002; 46(2): 167-191. doi: 10.21608/esju.2002.313797
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