Optimal Design For Nonlinear Response Models
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Optimal Design For Nonlinear Response Models
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Author : Valerii V. Fedorov
language : en
Publisher: CRC Press
Release Date : 2013-07-15
Optimal Design For Nonlinear Response Models written by Valerii V. Fedorov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-15 with Mathematics categories.
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors’ many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of the key ideas, using linear models as examples. Applying the linearization in the parameter space, it then covers nonlinear models and locally optimal designs as well as minimax, optimal on average, and Bayesian designs. The authors also discuss adaptive designs, focusing on procedures with non-informative stopping. The common goals of experimental design—such as reducing costs, supporting efficient decision making, and gaining maximum information under various constraints—are often the same across diverse applied areas. Ethical and regulatory aspects play a much more prominent role in biological, medical, and pharmaceutical research. The authors address all of these issues through many examples in the book.
Optimal Design For Nonlinear Response Models
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Author : Valerii V. Fedorov
language : en
Publisher: CRC Press
Release Date : 2013-07-15
Optimal Design For Nonlinear Response Models written by Valerii V. Fedorov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-15 with Mathematics categories.
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors' many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of
Moda 11 Advances In Model Oriented Design And Analysis
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Author : Joachim Kunert
language : en
Publisher: Springer
Release Date : 2016-06-06
Moda 11 Advances In Model Oriented Design And Analysis written by Joachim Kunert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-06 with Mathematics categories.
This volume contains pioneering contributions to both the theory and practice of optimal experimental design. Topics include the optimality of designs in linear and nonlinear models, as well as designs for correlated observations and for sequential experimentation. There is an emphasis on applications to medicine, in particular, to the design of clinical trials. Scientists from Europe, the US, Asia, Australia and Africa contributed to this volume of papers from the 11th Workshop on Model Oriented Design and Analysis.
Handbook Of Methods For Designing Monitoring And Analyzing Dose Finding Trials
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Author : John O'Quigley
language : en
Publisher: CRC Press
Release Date : 2017-04-27
Handbook Of Methods For Designing Monitoring And Analyzing Dose Finding Trials written by John O'Quigley and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-27 with Mathematics categories.
Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials gives a thorough presentation of state-of-the-art methods for early phase clinical trials. The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of early phase studies. The need to accelerate drug development in a rapidly evolving context of targeted therapies, immunotherapy, combination treatments and complex group structures has provided the stimulus to these advances. Typically, we deal with very small samples, sequential methods that need to be efficient, while, at the same time adhering to ethical principles due to the involvement of human subjects. Statistical inference is difficult since the standard techniques of maximum likelihood do not usually apply as a result of model misspecification and parameter estimates lying on the boundary of the parameter space. Bayesian methods play an important part in overcoming these difficulties, but nonetheless, require special consideration in this particular context. The purpose of this handbook is to provide an expanded summary of the field as it stands and also, through discussion, provide insights into the thinking of leaders in the field as to the potential developments of the years ahead. With this goal in mind we present: An introduction to the field for graduate students and novices A basis for more established researchers from which to build A collection of material for an advanced course in early phase clinical trials A comprehensive guide to available methodology for practicing statisticians on the design and analysis of dose-finding experiments An extensive guide for the multiple comparison and modeling (MCP-Mod) dose-finding approach, adaptive two-stage designs for dose finding, as well as dose–time–response models and multiple testing in the context of confirmatory dose-finding studies. John O’Quigley is a professor of mathematics and research director at the French National Institute for Health and Medical Research based at the Faculty of Mathematics, University Pierre and Marie Curie in Paris, France. He is author of Proportional Hazards Regression and has published extensively in the field of dose finding. Alexia Iasonos is an associate attending biostatistician at the Memorial Sloan Kettering Cancer Center in New York. She has over one hundred publications in the leading statistical and clinical journals on the methodology and design of early phase clinical trials. Dr. Iasonos has wide experience in the actual implementation of model based early phase trials and has given courses in scientific meetings internationally. Björn Bornkamp is a statistical methodologist at Novartis in Basel, Switzerland, researching and implementing dose-finding designs in Phase II clinical trials. He is one of the co-developers of the MCP-Mod methodology for dose finding and main author of the DoseFinding R package. He has published numerous papers on dose finding, nonlinear models and Bayesian statistics, and in 2013 won the Royal Statistical Society award for statistical excellence in the pharmaceutical industry.
12th International Symposium On Process Systems Engineering And 25th European Symposium On Computer Aided Process Engineering
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Author :
language : en
Publisher: Elsevier
Release Date : 2015-07-14
12th International Symposium On Process Systems Engineering And 25th European Symposium On Computer Aided Process Engineering written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-14 with Technology & Engineering categories.
25th European Symposium on Computer-Aided Process Engineering contains the papers presented at the 12th Process Systems Engineering (PSE) and 25th European Society of Computer Aided Process Engineering (ESCAPE) Joint Event held in Copenhagen, Denmark, 31 May - 4 June 2015. The purpose of these series is to bring together the international community of researchers and engineers who are interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE/CAPE community towards the sustainability of modern society. Contributors from academia and industry establish the core products of PSE/CAPE, define the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment, and health) and contribute to discussions on the widening scope of PSE/CAPE versus the consolidation of the core topics of PSE/CAPE. - Highlights how the Process Systems Engineering/Computer-Aided Process Engineering community contributes to the sustainability of modern society - Presents findings and discussions from both the 12th Process Systems Engineering (PSE) and 25th European Society of Computer-Aided Process Engineering (ESCAPE) Events - Establishes the core products of Process Systems Engineering/Computer Aided Process Engineering - Defines the future challenges of the Process Systems Engineering/Computer Aided Process Engineering community
Optimal Experimental Design
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Author : Jesús López-Fidalgo
language : en
Publisher: Springer Nature
Release Date : 2023-09-12
Optimal Experimental Design written by Jesús López-Fidalgo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-12 with Mathematics categories.
This textbook provides a concise introduction to optimal experimental design and efficiently prepares the reader for research in the area. It presents the common concepts and techniques for linear and nonlinear models as well as Bayesian optimal designs. The last two chapters are devoted to particular themes of interest, including recent developments and hot topics in optimal experimental design, and real-world applications. Numerous examples and exercises are included, some of them with solutions or hints, as well as references to the existing software for computing designs. The book is primarily intended for graduate students and young researchers in statistics and applied mathematics who are new to the field of optimal experimental design. Given the applications and the way concepts and results are introduced, parts of the text will also appeal to engineers and other applied researchers.
Trends In Mathematical Information And Data Sciences
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Author : Narayanaswamy Balakrishnan
language : en
Publisher: Springer Nature
Release Date : 2022-06-27
Trends In Mathematical Information And Data Sciences written by Narayanaswamy Balakrishnan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-27 with Technology & Engineering categories.
This book involves ideas/results from the topics of mathematical, information, and data sciences, in connection with the main research interests of Professor Pardo that can be summarized as Information Theory with Applications to Statistical Inference. This book is a tribute to Professor Leandro Pardo, who has chaired the Department of Statistics and OR of the Complutense University in Madrid, and he has been also President of the Spanish Society of Statistics and Operations Research. In this way, the contributions have been structured into three parts, which often overlap to a greater or lesser extent, namely Trends in Mathematical Sciences (Part I) Trends in Information Sciences (Part II) Trends in Data Sciences (Part III) The contributions gathered in this book have offered either new developments from a theoretical and/or computational and/or applied point of view, or reviews of recent literature of outstanding developments. They have been applied through nice examples in climatology, chemistry, economics, engineering, geology, health sciences, physics, pandemics, and socioeconomic indicators. Consequently, the intended audience of this book is mainly statisticians, mathematicians, computer scientists, and so on, but users of these disciplines as well as experts in the involved applications may certainly find this book a very interesting read.
Statistical Machine Learning For Engineering With Applications
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Author : Jürgen Franke
language : en
Publisher: Springer Nature
Release Date : 2024-10-08
Statistical Machine Learning For Engineering With Applications written by Jürgen Franke and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-08 with Mathematics categories.
This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For ease of reading, technical details are avoided as far as possible, and there is a particular emphasis on applicability, interpretation, reliability and limitations of the data-analytic methods in practice. To cover the common availability and types of data in engineering, training sets consisting of independent as well as time series data are considered. To cope with the scarceness of data in industrial problems, augmentation of training sets by additional artificial data, generated from physical models, as well as the combination of machine learning and expert knowledge of engineers are discussed. The methodological exposition is accompanied by several detailed case studies based on industrial projects covering a broad range of engineering applications from vehicle manufacturing, process engineering and design of materials to optimization of production processes based on image analysis. The focus is on fundamental ideas, applicability and the pitfalls of machine learning in industry and science, where data are often scarce. Requiring only very basic background in statistics, the book is ideal for self-study or short courses for engineering and science students.
Digital Therapeutics
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Author : Oleksandr Sverdlov
language : en
Publisher: CRC Press
Release Date : 2022-12-06
Digital Therapeutics written by Oleksandr Sverdlov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Mathematics categories.
One of the hallmarks of the 21st century medicine is the emergence of digital therapeutics (DTx)—evidence-based, clinically validated digital technologies to prevent, diagnose, treat, and manage various diseases and medical conditions. DTx solutions have been gaining interest from patients, investors, healthcare providers, health authorities, and other stakeholders because of the potential of DTx to deliver equitable, massively scalable, personalized and transformative treatments for different unmet medical needs. Digital Therapeutics: Scientific, Statistical, Clinical, and Regulatory Aspects is an unparalleled summary of the current scientific, statistical, developmental, and regulatory aspects of DTx which is poised to become the fastest growing area of the biopharmaceutical and digital medicine product development. This edited volume intends to provide a systematic exposition to digital therapeutics through 19 peer-reviewed chapters written by subject matter experts in this emerging field. This edited volume is an invaluable resource for business leaders and researchers working in public health, healthcare, digital health, information technology, and biopharmaceutical industries. It will be also useful for regulatory scientists involved in the review of DTx products, and for faculty and students involved in an interdisciplinary research on digital health and digital medicine. Key Features: Provides the taxonomy of the concepts and a navigation tool for the field of DTx. Covers important strategic aspects of the DTx industry, thereby helping investors, developers, and regulators gain a better appreciation of the potential value of DTx. Expounds on many existing and emerging state-of-the art scientific and technological tools, as well as data privacy, ethical and regulatory considerations for DTx product development. Presents several case studies of successful development of some of the most remarkable DTx products. Provides some perspectives and forward-looking statements on the future of digital medicine.
Optimal Design Of Experiments
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Author : Friedrich Pukelsheim
language : en
Publisher: SIAM
Release Date : 2006-04-01
Optimal Design Of Experiments written by Friedrich Pukelsheim and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-01 with Mathematics categories.
Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.