Composite quantile estimation in partial functional linear regression model with dependent errors

Ping Yu; Ting Li; Zhongyi Zhu; Zhongzhan Zhang

doi:10.1007/s00184-018-0699-3

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Composite quantile estimation in partial functional linear regression model with dependent errors

Ping Yu Ting Li Zhongyi Zhu Zhongzhan Zhang

Year: 2019 Journal: Metrika Vol: 82 (6)Pages: 633-656 Publisher: Springer Science+Business Media

DOI: 10.1007/s00184-018-0699-3

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Keywords:

Mathematics Quantile Autoregressive model Quantile regression Outlier Applied mathematics Asymptotic distribution Functional principal component analysis Principal component analysis Range (aeronautics) Rate of convergence Linear model Principal component regression Statistics Mathematical optimization Computer science

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Control Systems and Identification

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Composite quantile estimation in partial functional linear regression model with dependent errors

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