Forecasting PC-ARIMA models for functional data

被引：0

作者：

Valderrama, MJ ^{[1
]}

Ocaña, FA ^{[1
]}

Aguilera, AM ^{[1
]}

机构：

[1] Dept Stat & Operat Res, Granada 18071, Spain

来源：

COMPSTAT 2002: PROCEEDINGS IN COMPUTATIONAL STATISTICS | 2002年

关键词：

principal components; functional data; ARIMA; El nino;

D O I：

暂无

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：

This paper introduces an improvement on the forecasting models previously developed by the authors for continuous time series based on the PCA of the stochastic process by cutting series in seasonal periods. The new approach consists of modelling principal components as ARIMA processes and then to formulate a mixed PC-ARIMA model for the time series. This methodology is then applied to the climatic phenomenon known as El Nino.

引用

页码：25 / 36

页数：12

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