Uncertainty quantification in modeling HIV viral mechanics
We consider an in-host model for HIV-1 infection dynamics developed and validated with patient data in earlier work [7]. We revisit the earlier model in light of progress over the last several years in understanding HIV-1 progression in humans. We then consider statistical models to describe the da...
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| Format: | Article |
| Language: | English |
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AIMS Press
2015-05-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.937 |
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| author | H. T. Banks Robert Baraldi Karissa Cross Kevin Flores Christina McChesney Laura Poag Emma Thorpe |
| author_facet | H. T. Banks Robert Baraldi Karissa Cross Kevin Flores Christina McChesney Laura Poag Emma Thorpe |
| author_sort | H. T. Banks |
| collection | DOAJ |
| description | We consider an in-host model for HIV-1 infection dynamics developed and validated with patient data in earlier work [7]. We revisit the earlier model in light of progress over the last several years in understanding HIV-1 progression in humans. We then consider statistical models to describe the data and use these with residual plots in generalized least squares problems to develop accurate descriptions of the proper weights for the data. We use recent parameter subset selection techniques [5,6] to investigate the impact of estimated parameters on the corresponding selection scores. Bootstrapping and asymptotic theory are compared in the context of confidence intervals for the resulting parameter estimates. |
| format | Article |
| id | doaj-art-16898907d09444099e8fdbe4d3397156 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2015-05-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-16898907d09444099e8fdbe4d33971562025-01-24T02:33:19ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-05-0112593796410.3934/mbe.2015.12.937Uncertainty quantification in modeling HIV viral mechanicsH. T. Banks0Robert Baraldi1Karissa Cross2Kevin Flores3Christina McChesney4Laura Poag5Emma Thorpe6Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212We consider an in-host model for HIV-1 infection dynamics developed and validated with patient data in earlier work [7]. We revisit the earlier model in light of progress over the last several years in understanding HIV-1 progression in humans. We then consider statistical models to describe the data and use these with residual plots in generalized least squares problems to develop accurate descriptions of the proper weights for the data. We use recent parameter subset selection techniques [5,6] to investigate the impact of estimated parameters on the corresponding selection scores. Bootstrapping and asymptotic theory are compared in the context of confidence intervals for the resulting parameter estimates.https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.937bootstrapping.uncertainty quantificationparameter subset selectionasymptotic distributionsin-host hiv-1 progression models |
| spellingShingle | H. T. Banks Robert Baraldi Karissa Cross Kevin Flores Christina McChesney Laura Poag Emma Thorpe Uncertainty quantification in modeling HIV viral mechanics Mathematical Biosciences and Engineering bootstrapping. uncertainty quantification parameter subset selection asymptotic distributions in-host hiv-1 progression models |
| title | Uncertainty quantification in modeling HIV viral mechanics |
| title_full | Uncertainty quantification in modeling HIV viral mechanics |
| title_fullStr | Uncertainty quantification in modeling HIV viral mechanics |
| title_full_unstemmed | Uncertainty quantification in modeling HIV viral mechanics |
| title_short | Uncertainty quantification in modeling HIV viral mechanics |
| title_sort | uncertainty quantification in modeling hiv viral mechanics |
| topic | bootstrapping. uncertainty quantification parameter subset selection asymptotic distributions in-host hiv-1 progression models |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.937 |
| work_keys_str_mv | AT htbanks uncertaintyquantificationinmodelinghivviralmechanics AT robertbaraldi uncertaintyquantificationinmodelinghivviralmechanics AT karissacross uncertaintyquantificationinmodelinghivviralmechanics AT kevinflores uncertaintyquantificationinmodelinghivviralmechanics AT christinamcchesney uncertaintyquantificationinmodelinghivviralmechanics AT laurapoag uncertaintyquantificationinmodelinghivviralmechanics AT emmathorpe uncertaintyquantificationinmodelinghivviralmechanics |