A Suggested Nonparametric Bivariate Logistic Density Estimator with Application on the Productivity of Egyptian Wheat during 2019/2020

IF 0.3 Q4 MATHEMATICS
Samah M. Abo-El-hadid
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引用次数: 0

Abstract

Email: s_aboelhadid@yahoo.com Samah_2999@yahoo.com Abstract: In this study, the nonparametric standard logistic density estimator, introduced by Abo-El-Hadid (2018), is extended to the bivariate case. The multiplicative standard logistic distribution is used as a kernel function to derive the bivariate kernel estimator. The statistical properties of the resulting estimator are studied, which are: The asymptotic bias, variance, Mean Squared Error (MSE) and Integrated Mean Squared Error (IMSE); also, the optimal bandwidth is obtained. A simulation study is introduced to investigate the performance of the proposed estimator with other estimators. We also apply the proposed estimator to a real data set to estimate the bivariate density of the planted and productive areas of wheat in Egypt.
非参数双变量Logistic密度估计在2019/2020年埃及小麦产量中的应用
摘要:本研究将Abo-El-Hadid(2018)引入的非参数标准logistic密度估计器推广到二元情况。采用乘法标准logistic分布作为核函数,导出二元核估计量。研究了所得估计量的统计性质,包括:渐近偏差、方差、均方误差(MSE)和积分均方误差(IMSE);同时,获得了最优带宽。通过仿真研究,研究了该估计器与其他估计器的性能。我们还将提出的估计器应用于实际数据集,以估计埃及小麦种植和生产区域的二元密度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.70
自引率
33.30%
发文量
0
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