Fitting censored quantile regression by variable neighborhood search

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چکیده

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Fitting censored quantile regression by variable neighborhood search

Censored quantile regression models are very useful for the analysis of censored data when standard linear models are felt to be appropriate. However, fitting censored quantile regression is hard numerically due to the fact that the objective function that has to be minimized is not convex nor concave in regressors. The performance of standard methods is not satisfactory, in particular if a hig...

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ژورنال

عنوان ژورنال: Journal of Global Optimization

سال: 2015

ISSN: 0925-5001,1573-2916

DOI: 10.1007/s10898-015-0311-6