Open AccessAlmost Sure Convergence of The k-NN Regression Estimate under Mixing condition: التقارب شبه الأكيد لمقدّر انحدار الجوارات الـ K الأكثر قرباً تحت شرط المزج
Author(s) -
Mohamed Deribati Dema Ahmad Al-shakh
Publication year - 2022
Publication title -
al-mağallaẗ al-ʿarabiyyaẗ li-l-ʿulūm wa-našr abḥāṯ
Language(s) - English
Resource type - Journals
ISSN - 2518-5780
DOI - 10.26389/ajsrp.m190821
Subject(s) - estimator , mixing (physics) , convergence (economics) , statistics , mathematics , regression , mean squared error , regression function , k nearest neighbors algorithm , least squares function approximation , regression analysis , function (biology) , sample (material) , computer science , artificial intelligence , physics , thermodynamics , quantum mechanics , evolutionary biology , economics , biology , economic growth
In this work we will establish almost sure convergence for k-nearest neighbor estimate of the regression function under some mixing conditions. Our results will extend some previous results in the i.i.d case to the dependent case. In addition, we will conduct a simulation study using R software program to display the importance and influence of the sample size (n) on behavior of the estimator. For this purpose, the mean squares error criterion (MSE) was used.