Abstract
Due to an interpolation property the computation of censored quantile regression estimates corresponds to the solution of a large scale discrete optimization problem. The global optimization heuristic threshold accepting is used in comparison to other algorithms. It can improve the results considerably though it uses more computing time.
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© 1998 Springer-Verlag Berlin Heidelberg
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Fitzenberger, B., Winker, P. (1998). Using Threshold Accepting to Improve the Computation of Censored Quantile Regression. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_40
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DOI: https://doi.org/10.1007/978-3-662-01131-7_40
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
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