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DC Field | Value | Language |
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dc.contributor.author | Wu, TZ | - |
dc.contributor.author | Yu, K | - |
dc.contributor.author | Yu, Y | - |
dc.date.accessioned | 2014-09-01T10:04:12Z | - |
dc.date.available | 2014-09-01T10:04:12Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Journal of Multivariate Analysis, 101(7), 1607 - 1621, 2010 | en_US |
dc.identifier.issn | 0047-259X | - |
dc.identifier.uri | http://www.sciencedirect.com/science/article/pii/S0047259X10000333 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/8975 | - |
dc.description | This is the post-print version of the final paper published in Journal of Multivariate Analysis. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V. | en_US |
dc.description.abstract | Nonparametric quantile regression with multivariate covariates is a difficult estimation problem due to the “curse of dimensionality”. To reduce the dimensionality while still retaining the flexibility of a nonparametric model, we propose modeling the conditional quantile by a single-index function View the MathML sourceg0(xTγ0), where a univariate link function g0(⋅)g0(⋅) is applied to a linear combination of covariates View the MathML sourcexTγ0, often called the single-index. We introduce a practical algorithm where the unknown link function g0(⋅)g0(⋅) is estimated by local linear quantile regression and the parametric index is estimated through linear quantile regression. Large sample properties of estimators are studied, which facilitate further inference. Both the modeling and estimation approaches are demonstrated by simulation studies and real data applications. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Conditional quantile | en_US |
dc.subject | Dimension reduction | en_US |
dc.subject | Local polynomial smoothing | en_US |
dc.subject | Nonparametric model | en_US |
dc.subject | Semiparametric model | en_US |
dc.title | Single-index quantile regression | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.jmva.2010.02.003 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics | - |
pubs.organisational-data | /Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Mathematics/Mathematical Sciences | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Environmental, Health and Societies | - |
pubs.organisational-data | /Brunel/Brunel Staff by Institute/Theme/Institute of Environmental, Health and Societies/Health Economics | - |
Appears in Collections: | Dept of Mathematics Research Papers Mathematical Sciences |
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Notice.pdf | 39.47 kB | Adobe PDF | View/Open |
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