Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/26397
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | De Mulder, Wim | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.date.accessioned | 2018-07-23T10:14:02Z | - |
dc.date.available | 2018-07-23T10:14:02Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 87(7), p. 1429-1445 | - |
dc.identifier.issn | 0094-9655 | - |
dc.identifier.uri | http://hdl.handle.net/1942/26397 | - |
dc.description.abstract | Probabilistic sensitivity analysis (SA) allows to incorporate background knowledge on the considered input variables more easily than many other existing SA techniques. Incorporation of such knowledge is performed by constructing a joint density function over the input domain. However, it rarely happens that available knowledge directly and uniquely translates into such a density function. A naturally arising question is then to what extent the choice of density function determines the values of the considered sensitivity measures. In this paper we perform simulation studies to address this question. Our empirical analysis suggests some guidelines, but also cautions to practitioners in the field of probabilistic SA. | - |
dc.description.sponsorship | The authors acknowledge funding from the KU Leuven funded Geconcerteerde Onderzoeksacties (GOA) project 'New approaches to the social dynamics of long-term fertility change' [grant 2014-2018;GOA/14/001]. | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS LTD | - |
dc.rights | © 2016 Informa UK Limited, trading as Taylor & Francis Group | - |
dc.subject.other | probabilistic sensitivity analysis; agent-based models; Gaussian process emulation; mean effect; sensitivity index | - |
dc.subject.other | Probabilistic sensitivity analysis; agent-based models; Gaussian process emulation; mean effect; sensitivity index | - |
dc.title | A sensitivity analysis of probabilistic sensitivity analysis in terms of the density function for the input variables | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 1445 | - |
dc.identifier.issue | 7 | - |
dc.identifier.spage | 1429 | - |
dc.identifier.volume | 87 | - |
local.format.pages | 17 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [De Mulder, Wim; Molenberghs, Geert; Verbeke, Geert] Leuven Biostat & Stat Bioinformat Ctr L BioStat, Leuven, Belgium. [Molenberghs, Geert; Verbeke, Geert] Interuniv Inst Biostat & Stat Bioinformat I BioSt, Hasselt, Belgium. | - |
local.publisher.place | ABINGDON | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1080/00949655.2016.1270280 | - |
dc.identifier.isi | 000399503100010 | - |
item.fullcitation | De Mulder, Wim; MOLENBERGHS, Geert & VERBEKE, Geert (2017) A sensitivity analysis of probabilistic sensitivity analysis in terms of the density function for the input variables. In: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 87(7), p. 1429-1445. | - |
item.validation | ecoom 2018 | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.contributor | De Mulder, Wim | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | VERBEKE, Geert | - |
crisitem.journal.issn | 0094-9655 | - |
crisitem.journal.eissn | 1563-5163 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Molenberghs.pdf Restricted Access | Published version | 3.59 MB | Adobe PDF | View/Open Request a copy |
paper_Statistical_Computation_Simulation_2.pdf | Peer-reviewed author version | 1.11 MB | Adobe PDF | View/Open |
Page view(s)
64
checked on Sep 5, 2022
Download(s)
136
checked on Sep 5, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.