On multiple regression models with nonstationarity correlated errors

被引：4
作者：
Rao, SS [1 ]
机构：
[1] Heidelberg Univ, Inst Angew Math, D-69120 Heidelberg, Germany
来源：
BIOMETRIKA | 2004年 / 91卷 / 03期
关键词：
asymptotic normality; consistency; heteroscedastic errors; local least squares; local stationanity; multiple regression; nonstationary; temperature anomaly; time series;
D O I：
10.1093/biomet/91.3.645
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
We consider the estimation of parameters of a multiple regression model with nonstationary errors. We assume the nonstationary errors satisfy a time-dependent autoregressive process and describe a method for estimating the parameters of the regressors and the time-dependent autoregressive parameters. The parameters are rescaled as in nonparametric regression to obtain the asymptotic sampling properties of the estimators. The method is illustrated with an example taken from global temperature anomalies.
引用
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页码：645 / 659
页数：15
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