Quantile regression with censored data using generalized L1minimization
(1997) In Computational Statistics & Data Analysis 23(4). p.509-524- Abstract
- We propose a way to estimate a parametric quantile function when the dependent variable, e.g. the survival time, is censored. We discuss one way to do this, transforming the problem of finding the p-quantile for the true, uncensored, survival times into a problem of finding the q-quantile for the observed, censored, times. The q-value involves the distribution of the censoring times, which is unknown. The estimation of the quantile function is done using the asymmetric L1 technique with weights involving local Kaplan-Meier estimates of the distribution of the censoring limit.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1670834
- author
- Lindgren, Anna LU
- organization
- publishing date
- 1997
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Quantile regression, L1 minimization, Right censoring, Kaplan-Meier estimator
- in
- Computational Statistics & Data Analysis
- volume
- 23
- issue
- 4
- pages
- 509 - 524
- publisher
- Elsevier
- external identifiers
-
- scopus:0031555710
- ISSN
- 0167-9473
- DOI
- 10.1016/S0167-9473(96)00048-5
- language
- English
- LU publication?
- yes
- id
- f894d204-080d-49fb-a328-cc5466cb0e3c (old id 1670834)
- date added to LUP
- 2016-04-01 12:03:25
- date last changed
- 2022-01-26 22:12:52
@article{f894d204-080d-49fb-a328-cc5466cb0e3c, abstract = {{We propose a way to estimate a parametric quantile function when the dependent variable, e.g. the survival time, is censored. We discuss one way to do this, transforming the problem of finding the p-quantile for the true, uncensored, survival times into a problem of finding the q-quantile for the observed, censored, times. The q-value involves the distribution of the censoring times, which is unknown. The estimation of the quantile function is done using the asymmetric L1 technique with weights involving local Kaplan-Meier estimates of the distribution of the censoring limit.}}, author = {{Lindgren, Anna}}, issn = {{0167-9473}}, keywords = {{Quantile regression; L1 minimization; Right censoring; Kaplan-Meier estimator}}, language = {{eng}}, number = {{4}}, pages = {{509--524}}, publisher = {{Elsevier}}, series = {{Computational Statistics & Data Analysis}}, title = {{Quantile regression with censored data using generalized L1minimization}}, url = {{http://dx.doi.org/10.1016/S0167-9473(96)00048-5}}, doi = {{10.1016/S0167-9473(96)00048-5}}, volume = {{23}}, year = {{1997}}, }