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Methods for estimating a conditional distribution function

Hall, Peter; Wolff, Rodney; Yao, Qiwei

Description

Motivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation. It produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1. The second method involves an adjusted form of the Nadaraya-Watson...[Show more]

dc.contributor.authorHall, Peter
dc.contributor.authorWolff, Rodney
dc.contributor.authorYao, Qiwei
dc.date.accessioned2015-12-13T23:22:31Z
dc.date.available2015-12-13T23:22:31Z
dc.identifier.issn0162-1459
dc.identifier.urihttp://hdl.handle.net/1885/91488
dc.description.abstractMotivated by the problem of setting prediction intervals in time series analysis, we suggest two new methods for conditional distribution estimation. The first method is based on locally fitting a logistic model and is in the spirit of recent work on locally parametric techniques in density estimation. It produces distribution estimators that may be of arbitrarily high order but nevertheless always lie between 0 and 1. The second method involves an adjusted form of the Nadaraya-Watson estimator. It preserves the bias and variance properties of a class of second-order estimators introduced by Yu and Jones but has the added advantage of always being a distribution itself. Our methods also have application outside the time series setting; for example, to quantile estimation for independent data. This problem motivated the work of Yu and Jones.
dc.publisherAmerican Statistical Association
dc.sourceJournal of the American Statistical Association
dc.subjectKeywords: Absolutely regular; Bandwidth; Biased bootstrap; Conditional distribution; Kernel methods; Local linear methods; Local logistic methods; Nadaraya-Watson estimator; Prediction; Quantile estimation; Time series analysis; Weighted bootstrap
dc.titleMethods for estimating a conditional distribution function
dc.typeJournal article
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.citationvolume94
dc.date.issued1999
local.identifier.absfor020204 - Plasma Physics; Fusion Plasmas; Electrical Discharges
local.identifier.ariespublicationMigratedxPub22246
local.type.statusPublished Version
local.contributor.affiliationHall, Peter, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationWolff, Rodney, Queensland University of Technology
local.contributor.affiliationYao, Qiwei, University of London
local.bibliographicCitation.issue445
local.bibliographicCitation.startpage154
local.bibliographicCitation.lastpage163
dc.date.updated2015-12-12T09:11:22Z
local.identifier.scopusID2-s2.0-0442325055
CollectionsANU Research Publications

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