Uncertainty quantification in modeling HIV viral mechanics
| Autor: | Kevin B. Flores, Karissa L. Cross, Robert Baraldi, Harvey Thomas Banks, Laura Poag, Emma Thorpe, Christina McChesney |
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| Rok vydání: | 2015 |
| Předmět: |
CD4-Positive T-Lymphocytes
Anti-HIV Agents Context (language use) HIV Infections Generalized least squares Biology Residual Models Biological Statistics Applied mathematics Humans Uncertainty quantification Least-Squares Analysis Bootstrapping (statistics) Clinical Trials as Topic Models Statistical Applied Mathematics Uncertainty Statistical model General Medicine Viral Load Asymptotic theory (statistics) Confidence interval Computational Mathematics Modeling and Simulation HIV-1 RNA Viral Reverse Transcriptase Inhibitors General Agricultural and Biological Sciences Algorithms |
| Zdroj: | Mathematical biosciences and engineering : MBE. 12(5) |
| ISSN: | 1551-0018 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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