Empirical likelihood for composite quantile regression modeling

Peixin Zhao; Xiaoshuang Zhou; Lu Lin

doi:10.1007/s12190-014-0804-3

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Empirical likelihood for composite quantile regression modeling

Peixin Zhao Xiaoshuang Zhou Lu Lin

Year: 2014 Journal: Journal of Applied Mathematics and Computing Vol: 48 (1-2)Pages: 321-333 Publisher: Springer Science+Business Media

DOI: 10.1007/s12190-014-0804-3

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Keywords:

Quantile regression Mathematics Quasi-maximum likelihood Empirical likelihood Econometrics Quantile Statistics Theory of computation Regression analysis Maximum likelihood Expectation–maximization algorithm Algorithm

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Advanced Statistical Process Monitoring

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Empirical likelihood for composite quantile regression modeling

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