Inference for non-stationary time-series autoregression

被引：3

作者：

Zhou, Zhou ^{[1
]}

机构：

[1] Univ Toronto, Toronto, ON M5S 3G3, Canada

来源：

JOURNAL OF TIME SERIES ANALYSIS | 2013年 / 34卷 / 04期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Simultaneous confidence tubes; time-varying AR models; Gaussian approximation; locally stationary approximation; MODELS;

D O I：

10.1111/jtsa.12028

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The article considers simultaneous inference for a class of non-stationary autoregressive models where the model parameters are allowed to vary smoothly over time. Simultaneous confidence tubes with asymptotically correct coverage probabilities are constructed to assess the overall patterns and magnitudes of the parameter functions over time. Simulation studies are conducted, and a real time-series dataset is analyzed to demonstrate the usefulness of the proposed methodology.

引用

页码：508 / 516

页数：9

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