An algorithm for censored quantile regressions

Thanasis Stengos and Dianqin Wang ()
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Dianqin Wang: University of Guelph

Economics Bulletin, 2007, vol. 3, issue 1, 1-9

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C2 (search for similar items in EconPapers)
Date: 2007-01-09
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