@article{banks_baraldi_cross_flores_mcchesney_poag_thorpe_2015, title={UNCERTAINTY QUANTIFICATION IN MODELING HIV VIRAL MECHANICS}, volume={12}, ISSN={["1551-0018"]}, DOI={10.3934/mbe.2015.12.937}, abstractNote={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.}, number={5}, journal={MATHEMATICAL BIOSCIENCES AND ENGINEERING}, author={Banks, H. T. and Baraldi, Robert and Cross, Karissa and Flores, Kevin and Mcchesney, Christina and Poag, Laura and Thorpe, Emma}, year={2015}, month={Oct}, pages={937–964} }
 @inproceedings{baraldi_cross_mcchesney_poag_thorpe_flores_banks_2014, title={Uncertainty quantification for a model of HIV-1 patient response to antiretroviral therapy interruptions}, booktitle={2014 american control conference (acc)}, author={Baraldi, R. and Cross, K. and McChesney, C. and Poag, L. and Thorpe, E. and Flores, K. B. and Banks, H. T.}, year={2014}, pages={2753–2758} }