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http://hdl.handle.net/1942/34674
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DC Field | Value | Language |
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dc.contributor.author | VAN HEEL, Mareike | - |
dc.contributor.author | Dikta, Gerhard | - |
dc.contributor.author | BRAEKERS, Roel | - |
dc.date.accessioned | 2021-08-17T18:30:53Z | - |
dc.date.available | 2021-08-17T18:30:53Z | - |
dc.date.issued | 2021 | - |
dc.date.submitted | 2021-08-17T17:57:11Z | - |
dc.identifier.citation | Journal of the Korean Statistical Society, | - |
dc.identifier.uri | http://hdl.handle.net/1942/34674 | - |
dc.description.abstract | We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613-641, 1997). In contrast to Stute and Zhu's approach (2002) Stute & Zhu (Scandinavian J Statist 29:535-545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute & Zhu (Scandinavian J Statist 29:535-545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set. | - |
dc.description.abstract | We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613-641, 1997). In contrast to Stute and Zhu's approach (2002) Stute & Zhu (Scandinavian J Statist 29:535-545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute & Zhu (Scandinavian J Statist 29:535-545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set. | - |
dc.description.sponsorship | Projekt DEAL | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER HEIDELBERG | - |
dc.rights | © The Author(s) 2021 | - |
dc.subject.other | Binary regression model; Bootstrap based test; Goodness-of-fit test; | - |
dc.subject.other | Marked empirical process | - |
dc.title | Bootstrap based goodness-of-fit tests for binary multivariate regression models | - |
dc.type | Journal Contribution | - |
local.format.pages | 28 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | van Heel, M (corresponding author), Fachhsch Aachen, D-52428 Julich, Germany.; van Heel, M (corresponding author), Univ Hasselt, B-3500 Hasselt, Belgium. | - |
dc.description.notes | van-heel@fh-aachen.de; dikta@fh-aachen.de; roel.braekers@uhasselt.be | - |
local.publisher.place | TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1007/s42952-021-00142-4 | - |
dc.identifier.isi | WOS:000681182000001 | - |
local.provider.type | wosris | - |
local.uhasselt.uhpub | yes | - |
local.description.affiliation | [van Heel, Mareike; Dikta, Gerhard] Fachhsch Aachen, D-52428 Julich, Germany. | - |
local.description.affiliation | [van Heel, Mareike] Univ Hasselt, B-3500 Hasselt, Belgium. | - |
local.description.affiliation | [Braekers, Roel] Univ Hasselt, Data Sci Inst, Biostat 1, B-3500 Hasselt, Belgium. | - |
local.uhasselt.international | yes | - |
item.fulltext | With Fulltext | - |
item.fullcitation | VAN HEEL, Mareike; Dikta, Gerhard & BRAEKERS, Roel (2021) Bootstrap based goodness-of-fit tests for binary multivariate regression models. In: Journal of the Korean Statistical Society,. | - |
item.contributor | VAN HEEL, Mareike | - |
item.contributor | Dikta, Gerhard | - |
item.contributor | BRAEKERS, Roel | - |
item.accessRights | Open Access | - |
item.validation | ecoom 2022 | - |
crisitem.journal.issn | 1226-3192 | - |
crisitem.journal.eissn | 2005-2863 | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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VanHeel2021_Article_BootstrapBasedGoodness-of-fitT.pdf | Published version | 2.17 MB | Adobe PDF | View/Open |
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