Seasonality analysis of time series in partial linear models

被引：1

作者：

Shao, Q. ^{[1
]}

机构：

[1] Univ Toledo, Dept Math, Toledo, OH 43606 USA

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2009年 / 21卷 / 07期

关键词：

partial linear model; seasonal component; local linear estimation; mean integrated squared error; time-series cross-validation; REGRESSION MODELS;

D O I：

10.1080/10485250903108391

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：

Seasonality analysis is one of the classic topics in time series. This paper studies techniques for seasonality analysis when the trend function is unspecified. The asymptotic properties of the semiparametric estimators are derived, and an estimation algorithm is provided. The techniques are applied to making inference for the monthly global land-ocean temperature anomaly indexes.

引用

页码：827 / 837

页数：11

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