Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.

Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.

Bibliographic Details
Main Author: Zou, Yuanshu
Language:English
Published: University of Cincinnati / OhioLINK 2013
Subjects:
Statistics
robustify
wavelet
bayesian
pharmacokinetics
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197606
id ndltd-OhioLink-oai-etd.ohiolink.edu-ucin1378197606
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-ucin13781976062021-08-03T06:19:39Z Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling. Zou, Yuanshu Statistics robustify wavelet bayesian pharmacokinetics Parametric models are easy to fit and easy to interpret, however, they may not be sufficientfor modeling data arising from complex phenomenon. Nonparametric models allowflexible modeling but have the difficulties in interpreting and dealing with very few observations. In my dissertation, we propose a nonparametric extension to robustify parametric nonlinear regression models. We consider in particular pharmacokinetic models that define the nonlinear regression function indirectly as solution of an ordinary differential equation (ODE) system. We begin with a tentative parametric model, e.g., a compartment model, and define a a nonparametric neighborhood of the tentative model using wavelet decomposition. We do this by defining a suitable prior for the wavelet coefficients, centered around that of the parametric model, with the wavelet based nonparametric neighborhood as the support. We use Bayesian approach to fit the model, implementing wavelet thresholding proposed by Muller and Vidakovic [26]. We also extend our method to population pharmacokinetics. Our method is flexible enough to adapt to deviations from a standard nonlinear drug concentration profile allowing robust modeling and predictions. We illustrate the proposed approach using simulated and real data sets. 2013-09-16 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197606 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197606 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Statistics
robustify
wavelet
bayesian
pharmacokinetics
spellingShingle Statistics
robustify
wavelet
bayesian
pharmacokinetics
Zou, Yuanshu
Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
author Zou, Yuanshu
author_facet Zou, Yuanshu
author_sort Zou, Yuanshu
title Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
title_short Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
title_full Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
title_fullStr Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
title_full_unstemmed Robustifying a Non-Linear Model using Wavelets: A Bayesian Approach with an Application to Pharmacokinetics Modeling.
title_sort robustifying a non-linear model using wavelets: a bayesian approach with an application to pharmacokinetics modeling.
publisher University of Cincinnati / OhioLINK
publishDate 2013
url http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197606
work_keys_str_mv AT zouyuanshu robustifyinganonlinearmodelusingwaveletsabayesianapproachwithanapplicationtopharmacokineticsmodeling
_version_ 1719434841806602240

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