dc.contributor.advisor | Haslett, John | |
dc.contributor.author | Bhattacharya, Sourabh | |
dc.date.accessioned | 2019-04-29T14:22:24Z | |
dc.date.available | 2019-04-29T14:22:24Z | |
dc.date.issued | 2005 | |
dc.identifier.citation | Sourabh Bhattacharya, 'Importance resampling MCMC : a methodology for cross-validation in inverse problems and its applications in model assessment', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005, pp 168 | |
dc.identifier.other | THESIS 7691 | |
dc.identifier.uri | http://hdl.handle.net/2262/86211 | |
dc.description.abstract | This thesis presents a methodology for implementing cross-validation in the context of
Bayesian modelling of situations we loosely refer to as 'inverse problems'. It is motivated
by an example from palaeoclimatology in which scientists reconstruct past climates from
fossils in lake sediment. The inverse problem is then to build a model with which to make
statem ents about climate, given sediment. One natural aspect of this is to examine model
fit via cross-validation. In MCMC studies this can be computationally burdensome and our
procedure has attractive properties in this respect. We demonstrate that, in addition, it is
possible to take advantage of the flexibility inherent within the method to make it suitable
for exploring multimodal distributions. We also propose to construct useful reference distributions
using data obtained from cross-validation. Our proposals are illustrated using a
simulated data set and several real data sets. | |
dc.format | 1 volume | |
dc.language.iso | en | |
dc.publisher | Trinity College (Dublin, Ireland). School of Computer Science & Statistics | |
dc.relation.isversionof | http://stella.catalogue.tcd.ie/iii/encore/record/C__Rb12458005 | |
dc.subject | Statistics, Ph.D. | |
dc.subject | Ph.D. Trinity College Dublin | |
dc.title | Importance resampling MCMC : a methodology for cross-validation in inverse problems and its applications in model assessment | |
dc.type | thesis | |
dc.type.supercollection | thesis_dissertations | |
dc.type.supercollection | refereed_publications | |
dc.type.qualificationlevel | Doctoral | |
dc.type.qualificationname | Doctor of Philosophy (Ph.D.) | |
dc.rights.ecaccessrights | openAccess | |
dc.format.extentpagination | pp 168 | |
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