Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/29588
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vo, Brenda N | en |
dc.contributor.author | Drovandi, Christopher C | en |
dc.contributor.author | Pettitt, Anthony N | en |
dc.date.accessioned | 2020-10-27T23:27:16Z | - |
dc.date.available | 2020-10-27T23:27:16Z | - |
dc.date.issued | 2019-03 | - |
dc.identifier.citation | Bayesian Analysis, 14(1), p. 211-234 | en |
dc.identifier.issn | 1931-6690 | en |
dc.identifier.issn | 1936-0975 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/29588 | - |
dc.description.abstract | In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the computationally efficient semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. The parametric bootstrap approximation is used to form a proposal distribution in ABC algorithms to improve the computational efficiency. The new approach is demonstrated through the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. We found efficiency gains in two simulation studies, the univariate g-and-k quantile distribution, a toggle switch model in dynamic bionetworks, and in a stochastic model describing expanding melanoma cell colonies. | en |
dc.language | en | en |
dc.publisher | International Society for Bayesian Analysis | en |
dc.relation.ispartof | Bayesian Analysis | en |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | Bayesian Parametric Bootstrap for Models with Intractable Likelihoods | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1214/17-ba1071 | en |
dcterms.accessRights | Gold | en |
local.contributor.firstname | Brenda N | en |
local.contributor.firstname | Christopher C | en |
local.contributor.firstname | Anthony N | en |
local.relation.isfundedby | ARC | en |
local.subject.for2008 | 010401 Applied Statistics | en |
local.subject.for2008 | 010402 Biostatistics | en |
local.subject.for2008 | 010406 Stochastic Analysis and Modelling | en |
local.subject.seo2008 | 970101 Expanding Knowledge in the Mathematical Sciences | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | bvo3@une.edu.au | en |
local.output.category | C1 | en |
local.grant.number | DP110100159 | en |
local.grant.number | DE160100741 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 211 | en |
local.format.endpage | 234 | en |
local.identifier.scopusid | 85064600268 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 14 | en |
local.identifier.issue | 1 | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Vo | en |
local.contributor.lastname | Drovandi | en |
local.contributor.lastname | Pettitt | en |
dc.identifier.staff | une-id:bvo3 | en |
local.profile.orcid | 0000-0003-0943-9768 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/29588 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Bayesian Parametric Bootstrap for Models with Intractable Likelihoods | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.relation.grantdescription | ARC/DP110100159 | en |
local.relation.grantdescription | ARC/DE160100741 | en |
local.search.author | Vo, Brenda N | en |
local.search.author | Drovandi, Christopher C | en |
local.search.author | Pettitt, Anthony N | en |
local.uneassociation | Yes | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2019 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/aa935561-8b22-491c-ad5f-e64357571540 | en |
local.subject.for2020 | 461302 Computational complexity and computability | en |
local.subject.for2020 | 460501 Data engineering and data science | en |
local.subject.seo2020 | 220402 Applied computing | en |
local.codeupdate.date | 2022-03-03T14:30:32.485 | en |
local.codeupdate.eperson | bvo3@une.edu.au | en |
local.codeupdate.finalised | true | en |
local.original.for2020 | 490510 Stochastic analysis and modelling | en |
local.original.for2020 | 490502 Biostatistics | en |
local.original.for2020 | 490501 Applied statistics | en |
local.original.seo2020 | 280118 Expanding knowledge in the mathematical sciences | en |
Appears in Collections: | Journal Article School of Science and Technology |
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