Identifiability In Stochastic Models

Identifiability In Stochastic Models PDF Author: Bozzano G Luisa
Publisher: Academic Press
ISBN: 0128015268
Category : Mathematics
Languages : en
Pages : 271

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Book Description
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.

Identifiability In Stochastic Models

Identifiability In Stochastic Models PDF Author: Bozzano G Luisa
Publisher: Academic Press
ISBN: 0128015268
Category : Mathematics
Languages : en
Pages : 271

Get Book Here

Book Description
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.

Characterization and Identifiability Results in Some Stochastic Models

Characterization and Identifiability Results in Some Stochastic Models PDF Author: Theofanis Sapatinas
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


On a Problem of Non-identifiability Arising in Simple Stochastic Models for Stereological Counts

On a Problem of Non-identifiability Arising in Simple Stochastic Models for Stereological Counts PDF Author: P. S. Puri
Publisher:
ISBN:
Category :
Languages : en
Pages : 19

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Book Description


Stochastic Modelling of Social Processes

Stochastic Modelling of Social Processes PDF Author: Andreas Diekmann
Publisher: Academic Press
ISBN: 1483266567
Category : Mathematics
Languages : en
Pages : 352

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Book Description
Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data. This book is a valuable resource for social scientists and statisticians.

On certain Problems involving non-identifiability of distributions arising in stochastic modeling

On certain Problems involving non-identifiability of distributions arising in stochastic modeling PDF Author: Prem S. Puri
Publisher:
ISBN:
Category :
Languages : en
Pages : 17

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Book Description


Stochastic Models: Estimation and Control: v. 2

Stochastic Models: Estimation and Control: v. 2 PDF Author: Maybeck
Publisher: Academic Press
ISBN: 0080956513
Category : Mathematics
Languages : en
Pages : 307

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Book Description
Stochastic Models: Estimation and Control: v. 2

Stochastic Modelling and Control

Stochastic Modelling and Control PDF Author: Mark Davis
Publisher: Springer Science & Business Media
ISBN: 940094828X
Category : Science
Languages : en
Pages : 405

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Book Description
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.

Uncertainty Quantification and Stochastic Modeling with Matlab

Uncertainty Quantification and Stochastic Modeling with Matlab PDF Author: Eduardo Souza de Cursi
Publisher: Elsevier
ISBN: 0081004710
Category : Mathematics
Languages : en
Pages : 457

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Book Description
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

Stochastic Calculus and Stochastic Models

Stochastic Calculus and Stochastic Models PDF Author: E. J. McShane
Publisher: Academic Press
ISBN: 1483218775
Category : Mathematics
Languages : en
Pages : 252

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Book Description
Probability and Mathematical Statistics: A Series of Monographs and Textbooks: Stochastic Calculus and Stochastic Models focuses on the properties, functions, and applications of stochastic integrals. The publication first ponders on stochastic integrals, existence of stochastic integrals, and continuity, chain rule, and substitution. Discussions focus on differentiation of a composite function, continuity of sample functions, existence and vanishing of stochastic integrals, canonical form, elementary properties of integrals, and the Itô-belated integral. The book then examines stochastic differential equations, including existence of solutions of stochastic differential equations, linear differential equations and their adjoints, approximation lemma, and the Cauchy-Maruyama approximation. The manuscript takes a look at equations in canonical form, as well as justification of the canonical extension in stochastic modeling; rate of convergence of approximations to solutions; comparison of ordinary and stochastic differential equations; and invariance under change of coordinates. The publication is a dependable reference for mathematicians and researchers interested in stochastic integrals.

Stochastic Processes: Theory and Methods

Stochastic Processes: Theory and Methods PDF Author: D N Shanbhag
Publisher: Gulf Professional Publishing
ISBN: 9780444500144
Category : Mathematics
Languages : en
Pages : 990

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Book Description
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.