The theory of stochastic integration, also called the Ito calculus, has a large spectrum of applications in virtually every ...
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Lévy processes are the natural continuous-time analogue of random walks and form a rich class of stochastic processes around ...
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Lévy processes are the natural continuous-time analogue of random walks and form a rich class of stochastic processes around ...
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Kanban control systems bear a great potential to significantly improve operations. A company may reap the full benefits of ...
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Lagrangian expansions can be used to obtain numerous useful probability models, which have been applied to real life situations ...
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Lagrangian expansions can be used to obtain numerous useful probability models, which have been applied to real life situations ...
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This book describes in detail the practice of the Bayesian statistical approach using many examples chosen for their educational ...
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Since its inception in 1974, the level crossing approach for analyzing a large class of stochastic models has become increasingly ...
Lire la suiteincludes contributions originating from a conference held at Chapman University during November 14-19, 2017. It presents ...
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This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and ...
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The aim of this book is to give a systematic introduction to and overview of the relatively simple and popular linearization ...
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When applying the statistical theory of long range dependent (LRD) processes to economics, the strong complexity of macroeconomic ...
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The book provides a detailed introduction to maintenance policies, updates the reader on the current status of the field ...
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While the original works on Malliavin calculus aimed to study the smoothness of densities of solutions to stochastic differential ...
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Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
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Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
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Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be ...
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This book provides a comprehensive, self-contained and up-to-date treatment of the main topics in the theory of option pricing. ...
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This book highlights recent developments in mathematical control theory and its applications to finance. It presents a collection ...
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Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, ...
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