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Thanasis Stengos and Dianqin Wang
''An algorithm for censored quantile regressions''
( 2007, Vol. 3 No.1 )
In this paper, we present an algorithm for Censored Quantile Regression (CQR) estimation problems. Our method permits CQR estimation problems to be solved more efficiently and reliably than was hitherto possible. It guarantees to find a high quality estimator in O(k×n²) operations with k regressors and n observations, which is much less than the existing algorithms for CQR problems.
Keywords: Cencored Quantile Regression
JEL: C2 - Single Equation Models; Single Variables: General
Manuscript Received : Nov 27 2006 Manuscript Accepted : Jan 09 2007

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