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Identifiability In Stochastic Models
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Book Synopsis Identifiability In Stochastic Models by : Bozzano G Luisa
Download or read book Identifiability In Stochastic Models written by Bozzano G Luisa and published by Academic Press. This book was released on 2012-09-18 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of "characterization problems" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Book Synopsis Stochastic Processes: Theory and Methods by : D N Shanbhag
Download or read book Stochastic Processes: Theory and Methods written by D N Shanbhag and published by Gulf Professional Publishing. This book was released on 2001 with total page 990 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume in the series contains chapters on areas such as pareto processes, branching processes, inference in stochastic processes, Poisson approximation, Levy processes, and iterated random maps and some classes of Markov processes. Other chapters cover random walk and fluctuation theory, a semigroup representation and asymptomatic behavior of certain statistics of the Fisher-Wright-Moran coalescent, continuous-time ARMA processes, record sequence and their applications, stochastic networks with product form equilibrium, and stochastic processes in insurance and finance. Other subjects include renewal theory, stochastic processes in reliability, supports of stochastic processes of multiplicity one, Markov chains, diffusion processes, and Ito's stochastic calculus and its applications. c. Book News Inc.
Book Synopsis Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention by : W. Y. Tan
Download or read book Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention written by W. Y. Tan and published by World Scientific. This book was released on 2005 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Only book on extensive, deterministic models, statistic models, stochastic models and state space models and statistical methods for HIV epidemic involving IV drug usage and HIV epidemic in homosexual populations. - Provides most recent biological insights into HIV pathogenesis and HIV kinetics at the cellular level, and illustrates how to build up mathematical models based on these biological insights. - Only publication that provides in-depth analysis of HAART treatment protocols and discusses possible improvements to the HAART protocol. The book also provides connection between pharmacokinetics with treatment in HIV-infected individuals.
Download or read book Stochastic Systems written by P. R. Kumar and published by SIAM. This book was released on 2015-12-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.
Book Synopsis Stochastic Modelling and Control by : Mark Davis
Download or read book Stochastic Modelling and Control written by Mark Davis and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.
Book Synopsis Stochastic Models in Biology by : Narendra S. Goel
Download or read book Stochastic Models in Biology written by Narendra S. Goel and published by Elsevier. This book was released on 2013-10-22 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Models in Biology describes the usefulness of the theory of stochastic process in studying biological phenomena. The book describes analysis of biological systems and experiments though probabilistic models rather than deterministic methods. The text reviews the mathematical analyses for modeling different biological systems such as the random processes continuous in time and discrete in state space. The book also discusses population growth and extinction through Malthus' law and the work of MacArthur and Wilson. The text then explains the dynamics of a population of interacting species. The book also addresses population genetics under systematic evolutionary pressures known as deterministic equations and genetic changes in a finite population known as stochastic equations. The text then turns to stochastic modeling of biological systems at the molecular level, particularly the kinetics of biochemical reactions. The book also presents various useful equations such as the differential equation for generating functions for birth and death processes. The text can prove valuable for biochemists, cellular biologists, and researchers in the medical and chemical field who are tasked to perform data analysis.
Book Synopsis Identifiability and Regression Analysis of Biological Systems Models by : Paola Lecca
Download or read book Identifiability and Regression Analysis of Biological Systems Models written by Paola Lecca and published by Springer Nature. This book was released on 2020-03-05 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: This richly illustrated book presents the objectives of, and the latest techniques for, the identifiability analysis and standard and robust regression analysis of complex dynamical models. The book first provides a definition of complexity in dynamic systems by introducing readers to the concepts of system size, density of interactions, stiff dynamics, and hybrid nature of determination. In turn, it presents the mathematical foundations of and algorithmic procedures for model structural and practical identifiability analysis, multilinear and non-linear regression analysis, and best predictor selection. Although the main fields of application discussed in the book are biochemistry and systems biology, the methodologies described can also be employed in other disciplines such as physics and the environmental sciences. Readers will learn how to deal with problems such as determining the identifiability conditions, searching for an identifiable model, and conducting their own regression analysis and diagnostics without supervision. Featuring a wealth of real-world examples, exercises, and codes in R, the book addresses the needs of doctoral students and researchers in bioinformatics, bioengineering, systems biology, biophysics, biochemistry, the environmental sciences and experimental physics. Readers should be familiar with the fundamentals of probability and statistics (as provided in first-year university courses) and a basic grasp of R.
Book Synopsis Stochastic Models of Structural Plasma Turbulence by : Victor Yu Korolev
Download or read book Stochastic Models of Structural Plasma Turbulence written by Victor Yu Korolev and published by Walter de Gruyter. This book was released on 2006 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.
Book Synopsis Stochastic Models: Estimation and Control: by : Maybeck
Download or read book Stochastic Models: Estimation and Control: written by Maybeck and published by Academic Press. This book was released on 1982-08-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Models: Estimation and Control: v. 2
Book Synopsis Stochastic Models in Reliability Engineering by : Lirong Cui
Download or read book Stochastic Models in Reliability Engineering written by Lirong Cui and published by CRC Press. This book was released on 2020-09-01 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years. The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems. The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, and dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field. The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, and experiments and applied probability and statistics.
Book Synopsis An Introduction to Stochastic Modeling by : Howard M. Taylor
Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor and published by Academic Press. This book was released on 2014-05-10 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
Book Synopsis Identifiability of Parametric Models by : E. Walter
Download or read book Identifiability of Parametric Models written by E. Walter and published by Elsevier. This book was released on 2014-05-23 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identifiability of Parametric Models provides a comprehensive presentation of identifiability. This book is divided into 11 chapters. Chapter 1 reviews the basic methods for structural identifiability testing. The methods that deal with large-scale models and propose conjectures on global identifiability are considered in Chapter 2, while the problems of initial model selection and generating the set of models that have the exact same input-output behavior are evaluated in Chapter 3. Chapters 4 and 5 cover nonlinear models. The relations between identifiability and the well-posedness of the estimation problem are analyzed in Chapter 6, followed by a description of the algebraic manipulations required for testing a model for structural controllability, observability, identifiability, or distinguishability in chapter 7. The rest of the chapters are devoted to the relations between identifiability and parameter uncertainty. This publication is beneficial to students and researchers aiming to acquire knowledge of the identifiability of parametric models.
Book Synopsis Uncertainty Quantification and Stochastic Modeling with Matlab by : Eduardo Souza de Cursi
Download or read book Uncertainty Quantification and Stochastic Modeling with Matlab written by Eduardo Souza de Cursi and published by Elsevier. This book was released on 2015-04-09 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with many real-world applications within statistics, mathematics, probability and engineering, but also within the natural sciences. Literature on the topic has up until now been largely based on polynomial chaos, which raises difficulties when considering different types of approximation and does not lead to a unified presentation of the methods. Moreover, this description does not consider either deterministic problems or infinite dimensional ones. This book gives a unified, practical and comprehensive presentation of the main techniques used for the characterization of the effect of uncertainty on numerical models and on their exploitation in numerical problems. In particular, applications to linear and nonlinear systems of equations, differential equations, optimization and reliability are presented. Applications of stochastic methods to deal with deterministic numerical problems are also discussed. Matlab® illustrates the implementation of these methods and makes the book suitable as a textbook and for self-study. Discusses the main ideas of Stochastic Modeling and Uncertainty Quantification using Functional Analysis Details listings of Matlab® programs implementing the main methods which complete the methodological presentation by a practical implementation Construct your own implementations from provided worked examples
Book Synopsis Stochastic Models in Reliability by : Terje Aven
Download or read book Stochastic Models in Reliability written by Terje Aven and published by Springer Science & Business Media. This book was released on 2008-01-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive up-to-date presentation of some of the classical areas of reliability, based on a more advanced probabilistic framework using the modern theory of stochastic processes. This framework allows analysts to formulate general failure models, establish formulae for computing various performance measures, as well as determine how to identify optimal replacement policies in complex situations.
Book Synopsis Stochastic Modeling of Scientific Data by : Peter Guttorp
Download or read book Stochastic Modeling of Scientific Data written by Peter Guttorp and published by CRC Press. This book was released on 2018-03-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.
Book Synopsis System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models by : Salman Zaidi
Download or read book System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models written by Salman Zaidi and published by kassel university press GmbH. This book was released on 2019-02-22 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some novel approaches to estimate Nonlinear Output Error (NOE) models using TS fuzzy models for a class of nonlinear dynamic systems having variability in their outputs is presented in this dissertation. Instead of using unrealistic assumptions about uncertainty, the most common of which is normality, the proposed methodology tends to capture effects caused by the real uncertainty observed in the data. The methodology requires that the identification method must be repeated offline a number of times under similar conditions. This leads to multiple inputoutput time series from the underlying system. These time series are preprocessed using the techniques of statistics and probability theory to generate the envelopes of response at each time instant. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. The proposed identification algorithm provides for a model for predicting the center-valued response as well as envelopes as the measure of uncertainty in system output.
Book Synopsis 2019-20 MATRIX Annals by : Jan de Gier
Download or read book 2019-20 MATRIX Annals written by Jan de Gier and published by Springer Nature. This book was released on 2021-02-10 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATRIX is Australia’s international and residential mathematical research institute. It facilitates new collaborations and mathematical advances through intensive residential research programs, each 1-4 weeks in duration. This book is a scientific record of the ten programs held at MATRIX in 2019 and the two programs held in January 2020: · Topology of Manifolds: Interactions Between High and Low Dimensions · Australian-German Workshop on Differential Geometry in the Large · Aperiodic Order meets Number Theory · Ergodic Theory, Diophantine Approximation and Related Topics · Influencing Public Health Policy with Data-informed Mathematical Models of Infectious Diseases · International Workshop on Spatial Statistics · Mathematics of Physiological Rhythms · Conservation Laws, Interfaces and Mixing · Structural Graph Theory Downunder · Tropical Geometry and Mirror Symmetry · Early Career Researchers Workshop on Geometric Analysis and PDEs · Harmonic Analysis and Dispersive PDEs: Problems and Progress The articles are grouped into peer-reviewed contributions and other contributions. The peer-reviewed articles present original results or reviews on a topic related to the MATRIX program; the remaining contributions are predominantly lecture notes or short articles based on talks or activities at MATRIX.
