Stochastic Epidemic Models with Inference, 

Автор: Oksendal
Название: Stochastic Differential Equations
ISBN: 3540047581 ISBN-13(EAN): 9783540047582
Издательство: Springer
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Цена: 54820.00 T
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Описание: Gives an introduction to the basic theory of stochastic calculus and its applications. This book offers examples in order to motivate and illustrate the theory and show its importance for many applications in for example economics, biology and physics.

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 38010.00 T
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Автор: Gulisashvili
Название: Analytically Tractable Stochastic Stock Price Models
ISBN: 3642312136 ISBN-13(EAN): 9783642312137
Издательство: Springer
Цена: 37170.00 T
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Описание: For instance, in the Hull-White model the volatility process is a geometric Brownian motion, the Stein-Stein model uses an Ornstein-Uhlenbeck process as the stochastic volatility, and in the Heston model a Cox-Ingersoll-Ross process governs the behavior of the volatility.

Автор: Malempati M. Rao
Название: Stochastic Processes - Inference Theory
ISBN: 3319121715 ISBN-13(EAN): 9783319121710
Издательство: Springer
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Цена: 102480.00 T
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Описание: This is the revised and enlarged 2nd edition of the authors` original text, which was intended to be a modest complement to Grenander`s fundamental memoir on stochastic processes and related inference theory.

Название: Statistical Inference in Stochastic Processes
ISBN: 0367403072 ISBN-13(EAN): 9780367403072
Издательство: Taylor&Francis
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Цена: 67360.00 T
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Описание: Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that determine the drift and the jump mechanism of a di

Автор: Jean-Pierre Gabriel; Claude Lefevre; Philippe Pica
Название: Stochastic Processes in Epidemic Theory
ISBN: 3540525718 ISBN-13(EAN): 9783540525714
Издательство: Springer
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Цена: 74530.00 T
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Описание: This collection of papers gives a representative cross-selectional view of recent developments in the field. Lefevre, 17 other research papers look at stochastic modeling of epidemics, both from a theoretical and a statistical point of view. Some look more specifically at a particular disease such as AIDS, malaria, schistosomiasis and diabetes.

Автор: Karatzas
Название: Brownian Motion and Stochastic Calculus
ISBN: 0387976558 ISBN-13(EAN): 9780387976556
Издательство: Springer
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Цена: 46540.00 T
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Описание: This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large number of problems and exercises.

Автор: Martin L. Puterman
Название: Markov Decision Processes: Discrete Stochastic Dynamic Programming
ISBN: 0471727822 ISBN-13(EAN): 9780471727828
Издательство: Wiley
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Цена: 137230.00 T
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Описание: This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.

Автор: Stefano M. Iacus
Название: Simulation and Inference for Stochastic Differential Equations
ISBN: 1441926070 ISBN-13(EAN): 9781441926074
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book covers a highly relevant topic that is of wide interest, especially in finance, engineering and computational biology. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners with minimal mathematical background.

Автор: Stefano M. Iacus; Nakahiro Yoshida
Название: Simulation and Inference for Stochastic Processes with YUIMA
ISBN: 3319555677 ISBN-13(EAN): 9783319555676
Издательство: Springer
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Цена: 46570.00 T
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Описание: The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Levy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes.