Joint detection for functional polynomial regression with autoregressive errors-Reference-Cited by-同舟云学术

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Joint detection for functional polynomial regression with autoregressive errors

Published:2016-05-27 Issue:16 Volume:46 Page:7837-7854
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Zhang Tao¹²,Dai Pengjie³,Zhang Qingzhao⁴

Affiliation:

1. School of Science, Guangxi University of Science and Technology, Liuzhou, China

2. Guangxi Colleges and Universities Key Laboratory of Mathematics and Statistical Model, Guilin, China

3. School of Business, Renmin University of China, Beijing, China

4. School of Economics and the Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2015.1096384

Reference29 articles.

1. A Bayesian analysis of the minimum AIC procedure

2. Nonparametric time series prediction: A semi-functional partial linear modeling

3. Consistency of the regression estimator with functional data under long memory conditions

4. Order selection for linear time series models: a review

5. Time Series: Theory and Methods

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