The ARHD model

被引：10

作者：

Mas, Andre

Pumo, Besnik

机构：

[1] Univ Montpellier 2, Dept Math, F-34095 Montpellier 5, France

[2] INH Angers, Unite Stat, UMR A462 SAGAH, Angers, France

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2007年 / 137卷 / 02期

关键词：

ARHD model; functional data; continuous-time prediction; Wong process; ENSO Sobolev space;

D O I：

10.1016/j.jspi.2005.12.006

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We introduce and study a new model for functional data. The ARHD is an autoregressive model in which the first order derivative of the random curves appears explicitly. Convergent estimates are obtained through an original double penalization method. The prediction method is applied to a real set of data already studied in the literature. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：538 / 553

页数：16

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