Download or read book A Simulation Based Comparison Between Parametric and Nonparametric Estimation Methods in PBPK Models written by and published by . This book was released on 2004 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: We compare parametric and nonparametric estimation methods in the context of PBPK modeling using simulation studies. We implement a Monte Carlo Markov Chain simulation technique in the parametric method, and a functional analytical approach to estimate the probability distribution function directly in the nonparametric method. The simulation results suggest an advantage for the parametric method when the underlying model can capture the true population distribution. On the other hand, our calculations demonstrate some advantages for a nonparametric approach since it is a more cautious (and hence safer) way to assess the distribution when one does not have sufficient knowledge to assume a population distribution form or parametrization. The parametric approach has obvious advantages when one has significant a priori information on the distributions sought, although when used in the nonparametric method, prior information can also significantly facilitate estimation.

Download or read book Nonparametric Function Estimation Modeling and Simulation written by James R. Thompson and published by SIAM. This book was released on 1990-01-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topics emphasized include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions.

Download or read book Inverse Problems Control and Modeling in the Presence of Uncertainty written by Harvey Thomas Banks and published by . This book was released on 2007 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We report progress on the development of methods in a number of specific areas of application including static, non-cooperative games related to counter- and counter-counter-electromagnetic interrogation of targets, modeling of complex viscoelastic polymeric materials, stochastic and deterministic models for complex networks and development of inverse problem methodologies (generalized sensitivity functions; asymptotic standard errors) for estimation of infinite dimensional functional parameters including probability measures and temporal/spatial dependent functions in complex nonlinear dynamical systems. These efforts are part of our fundamental research in a modeling, estimation and control methodology (theoretical, statistical and computational) for systems in the presence of major model and observation uncertainties.

Download or read book Mathematical Reviews written by and published by . This book was released on 2005 with total page 1608 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Functional Estimation and Related Topics written by G.G Roussas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.

Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by Springer Science & Business Media. This book was released on 1999-08-05 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.

Download or read book A Note on Nonparametric Estimation With Constructed Variables and Generated Regressors written by Stefan Sperlich and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article gives the asymptotic properties for nonparametric kernel based density and regression estimators when one of the variables, respectively regressors, had to be pre-estimated. Those variables are known as constructed variables or generatedregressors, and their impact on the -nal estimator is well studied in the fully para-metric context. The problem of making inference based on predicted rather than on observed values is quite frequent in econometrics and applied economics. The results are derived in such a way that the pre-estimation steps could be performed by any con-sistent nonparametric or parametric method. The case of parametric estimation with nonparametric predictors is discussed, as well. In most cases it is obvious and mathematically straightforward how to extend the results to semiparametric models or to other nonparametric smoothing methods. We also study the performance of nonparametric estimators with constructed variables by simulations and compare the numerical to our theoretical results.

Download or read book Non Parametric Estimation Under Strong Dependence written by Zhibiao Zhao and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance.

Download or read book Nonparametric Estimation and Specification Testing in Nonstationary Time Series Models written by Jiti Gao and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we consider both estimation and testing problems in a nonlinear time series model with nonstationarity. A nonparametric estimation method is proposed to estimate a sequence of nonparametric “distance functions”. We also propose a test statistic to test whether the regression function is of a known parametric nonlinear form. The power function of the proposed nonparametric test is studied and an asymptotic distribution of the test statistic is shown to depend on the asymptotic behavior of the “distance function” under a sequence of general semiparametric local alternatives. The asymptotic theory developed in this paper differs from existing work on nonparametric estimation and specification testing in the stationary time series case. In order to implement the proposed test in practice, a computer-intensive bootstrap simulation procedure is proposed and asymptotic approximations for both the size and power functions are established. Furthermore, the bandwidth involved in the test statistic is selected by maximizing the power function while the size function is controlled by a significance level. Meanwhile, both simulated and real data examples are provided to illustrate the proposed approach.

Download or read book Robust Nonparametric and Semiparametric Modeling written by Bo Kai and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, several new statistical procedures in nonparametric and semiparametric models are proposed. The concerns of the research are efficiency, robustness and sparsity. In Chapter 3, we propose complete composite quantile regression (CQR) procedures for estimating both the regression function and its derivatives in fully nonparametric regression models by using local smoothing techniques. The CQR estimator was recently proposed by Zou and Yuan (2008) for estimating the regression coefficients in the classical linear regression model. The asymptotic theory of the proposed estimator was established. We show that, compared with the classical local linear least squares estimator, the new method can significantly improve the estimation efficiency of the local linear least squares estimator for commonly used non-normal error distributions, and at the same time, the loss in efficiency is at most 8.01% in the worst case scenario. In Chapter 4, we further consider semiparametric models. The complexity of semiparametric models poses new challenges to parametric inferences and model selection that frequently arise from real applications. We propose new robust inference procedures for the semiparametric varying-coefficient partially linear model. We first study a quantile regression estimate for the nonparametric varying-coefficient functions and the parametric regression coefficients. To improve efficiency, we further develop a composite quantile regression procedure for both parametric and nonparametric components. To achieve sparsity, we develop a variable selection procedure for this model to select significant variables. We study the sampling properties of the resulting quantile regression estimate and composite quantile regression estimate. With proper choices of penalty functions and regularization parameters, we show the proposed variable selection procedure possesses the oracle property in the terminology of Fan and Li (2001). In Chapter 5, we propose a novel estimation procedure for varying coefficient models based on local ranks. By allowing the regression coefficients to change with certain covariates, the class of varying coefficient models offers a flexible semiparametric approach to modeling nonlinearity and interactions between covariates. Varying coefficient models are useful nonparametric regression models and have been well studied in the literature. However, the performance of existing procedures can be adversely influenced by outliers. The new procedure provides a highly efficient and robust alternative to the local linear least squares method and can be conveniently implemented using existing R software packages. We study the sample properties of the proposed procedure and establish the asymptotic normality of the resulting estimate. We also derive the asymptotic relative efficiency of the proposed local rank estimate to the local linear estimate for the varying coefficient model. The gain of the local rank regression estimate over the local linear regression estimate can be substantial. We further develop nonparametric inferences for the rank-based method. Monte Carlo simulations are conducted to access the finite sample performance of the proposed estimation procedure. The simulation results are promising and consistent with our theoretical findings. All the proposed procedures are supported by intensive finite sample simulation studies and most are illustrated with real data examples.

Download or read book Environmental Health Perspectives written by and published by . This book was released on 1993 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Bioequivalence Testing written by Sarfaraz K. Niazi and published by CRC Press. This book was released on 2007-08-22 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the generic pharmaceutical industry continues to grow and thrive, so does the need to conduct efficient and successful bioequivalence studies. In recent years, there have been significant changes to the statistical models for evaluating bioequivalence, and advances in the analytical technology used to detect drug and metabolite levels have made

Download or read book Cumulated Index Medicus written by and published by . This book was released on 2000 with total page 1840 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Index Medicus written by and published by . This book was released on 2001 with total page 1736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.

Download or read book Individualized Drug Therapy for Patients written by Roger W Jelliffe and published by Academic Press. This book was released on 2016-11-15 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Individualized Drug Therapy for Patients: Basic Foundations, Relevant Software and Clinical Applications focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal. This book highlights the best methods that enable individualized drug therapy and provides specific examples on how to incorporate these approaches using software that has been developed for this purpose. The book discusses where individualized therapy is currently and offers insights to the future. Edited by Roger Jelliffe, MD and Michael Neely, MD, renowned authorities in individualized drug therapy, and with chapters written by international experts, this book provides clinical pharmacologists, pharmacists, and physicians with a valuable and practical resource that takes drug therapy away from a memorized ritual to a thoughtful quantitative process aimed at optimizing therapy for each individual patient. 2018 PROSE Awards - Honorable Mention, Clinical Medicine: Association of American Publishers Uses pharmacokinetic approaches as the tools with which therapy is individualized Provides examples using specific software that illustrate how best to apply these approaches and to make sense of the more sophisticated mathematical foundations upon which this book is based Incorporates clinical cases throughout to illustrate the real-world benefits of using these approaches Focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal

Download or read book Handbook of Bioequivalence Testing Second Edition written by Sarfaraz K. Niazi and published by CRC Press. This book was released on 2014-10-29 with total page 1012 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the generic pharmaceutical industry continues to grow and thrive, so does the need to conduct adequate, efficient bioequivalence studies. In recent years, there have been significant changes to the statistical models for evaluating bioequivalence. In addition, advances in the analytical technology used to detect drug and metabolite levels have made bioequivalence testing more complex. The second edition of Handbook of Bioequivalence Testing has been completely updated to include the most current information available, including new findings in drug delivery and dosage form design and revised worldwide regulatory requirements. New topics include: A historical perspective on generic pharmaceuticals New guidelines governing submissions related to bioequivalency studies, along with therapeutic code classifications Models of noninferiority Biosimilarity of large molecule drugs Bioequivalence of complementary and alternate medicines Bioequivalence of biosimilar therapeutic proteins and monoclonal antibodies New FDA guidelines for bioanalytical method validation Outsourcing and monitoring of bioequivalence studies The cost of generic drugs is rising much faster than in the past, partly because of the increased costs required for approval—including those for bioequivalence testing. There is a dire need to re-examine the science behind this type of testing to reduce the burden of development costs—allowing companies to develop generic drugs faster and at a lower expense. The final chapter explores the future of bioequivalence testing and proposes radical changes in the process of biowaivers. It suggests how the cost of demonstrating bioequivalence can be reduced through intensive analytical investigation and proposes that regulatory agencies reduce the need for bioequivalence studies in humans. Backed by science and updated with the latest research, this book is destined to spark continued debate on the efficacy of the current bioequivalence testing paradigm.

Download or read book Pharmacokinetic Pharmacodynamic Modeling and Simulation written by Peter L. Bonate and published by Springer Science & Business Media. This book was released on 2006-05-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: A natural hierarchy exists in pharmacokinetic-pharmacodynamic modeling culminating in population pharmacokinetic models, which are a specific type of nonlinear mixed effects model. The purpose of this book is to present through theory and example how to develop pharmacokinetic models, both at an individual and population level. In order to do so, however, one must first understand linear models and then build to nonlinear models followed by linear mixed effects models and then ultimately nonlinear mixed effects models. This book develops in that manner – each chapter builds upon previous chapters by first presenting the theory and then illustrating the theory using published data sets and actual data sets that were used in the development of new chemical entities collected by the author during his years in industry. A key feature of the book is the process of modeling. Most books and manuscripts often present the final model never showing how the model evolved. In this book all examples are presented in an evolutionary manner.