A Comparison Between New Modification of ANWK and Classical ANWK Methods in Nonparametric Regression A Simulation Study

T. Kahwachi, Wasfi (2021) A Comparison Between New Modification of ANWK and Classical ANWK Methods in Nonparametric Regression A Simulation Study. Cihan University-Erbil Scientific Journal, 5 (2).

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Abstract

Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaraya-Watson kernel estimator (NWK) is one of the most important nonparametric kernel estimator that is often used in regression models with a fixed bandwidth. In this article, we consider the four new Proposed Adaptive Nadaraya-Watson Kernel Regression Estimators (Interquartile Range, Standard Deviation, Mean Absolute Devotion, and Median Absolute Deviation) rather than (Fixed Bandwidth, Adaptive Geometric, Adaptive Mean, Adaptive Range, and Adaptive Median). The outcomes in both simulation and actual data in Leukemia Cancer show that the four new ANW Kernel Estimators (Interquartile Range, Standard Deviation, Mean Absolute devotion, and Median Absolute Deviation) is more effective than the kernel estimations with fixed bandwidth in previous studies using Mean Square Error (MSE) Criterion.

Item Type: Article
Uncontrolled Keywords: Non-parametric Regression, Kernel Regression, New ANW Estimators, Leukemia Cancer, AML
Subjects: H Social Sciences > HB Economic Theory
Q Science > Q Science (General)
R Medicine > R Medicine (General)
Depositing User: ePrints deposit
Date Deposited: 14 Feb 2022 07:54
Last Modified: 14 Feb 2022 07:54
URI: http://eprints.tiu.edu.iq/id/eprint/813

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