函数拟相关时间序列数据单指标回归模型中的k近邻方法

IF 1.4 3区数学 Q1 MATHEMATICS

Revista Matematica Complutense Pub Date : 2022-07-06 DOI:10.1007/s13163-022-00436-z

S. Bouzebda, Ali Laksaci, Mustapha Mohammedi

引用次数: 5

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

The k-nearest neighbors method in single index regression model for functional quasi-associated time series data

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The k-nearest neighbors method in single index regression model for functional quasi-associated time series data

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来源期刊

Revista Matematica Complutense 数学-数学

CiteScore

2.30

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Revista Matemática Complutense is an international research journal supported by the School of Mathematics at Complutense University in Madrid. It publishes high quality research and survey articles across pure and applied mathematics. Fields of interests include: analysis, differential equations and applications, geometry, topology, algebra, statistics, computer sciences and astronomy. This broad interest is reflected in our interdisciplinary editorial board which is comprised of over 30 internationally esteemed researchers in diverse areas. The Editorial Board of Revista Matemática Complutense organizes the “Santaló Lecture”, a yearly event where a distinguished mathematician is invited to present a lecture at Complutense University and contribute to the journal. Past lecturers include: Charles T.C. Wall, Jack K. Hale, Hans Triebel, Marcelo Viana, Narayanswamy Balakrishnan, Nigel Kalton, Alfio Quarteroni, David E. Edmunds, Giuseppe Buttazzo, Juan L. Vázquez, Eduard Feireisl, Nigel Hitchin, Lajos Horváth, Hélène Esnault, Luigi Ambrosio, Ignacio Cirac and Bernd Sturmfels. The Santaló Lecturer for 2019 will be Noel Cressie from National Institute for Applied Statistics Research Australia (NIASRA), University of Wollongong.