Limit Theorems For Stochastic Processes
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Author | : Jean Jacod |
Publisher | : Springer Science & Business Media |
Total Pages | : 620 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 3662025140 |
Download Limit Theorems for Stochastic Processes Book in PDF, Epub and Kindle
Initially the theory of convergence in law of stochastic processes was developed quite independently from the theory of martingales, semimartingales and stochastic integrals. Apart from a few exceptions essentially concerning diffusion processes, it is only recently that the relation between the two theories has been thoroughly studied. The authors of this Grundlehren volume, two of the international leaders in the field, propose a systematic exposition of convergence in law for stochastic processes, from the point of view of semimartingale theory, with emphasis on results that are useful for mathematical theory and mathematical statistics. This leads them to develop in detail some particularly useful parts of the general theory of stochastic processes, such as martingale problems, and absolute continuity or contiguity results. The book contains an elementary introduction to the main topics: theory of martingales and stochastic integrales, Skorokhod topology, etc., as well as a large number of results which have never appeared in book form, and some entirely new results. It should be useful to the professional probabilist or mathematical statistician, and of interest also to graduate students.
Author | : Dmitrii S. Silvestrov |
Publisher | : Springer Science & Business Media |
Total Pages | : 408 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 0857293907 |
Download Limit Theorems for Randomly Stopped Stochastic Processes Book in PDF, Epub and Kindle
This volume is the first to present a state-of-the-art overview of this field, with many results published for the first time. It covers the general conditions as well as the basic applications of the theory, and it covers and demystifies the vast and technically demanding Russian literature in detail. Its coverage is thorough, streamlined and arranged according to difficulty.
Author | : Dimitri Silvestrov |
Publisher | : |
Total Pages | : 416 |
Release | : 2014-01-15 |
Genre | : |
ISBN | : 9780857293916 |
Download Limit Theorems for Randomly Stopped Stochastic Processes Book in PDF, Epub and Kindle
Author | : |
Publisher | : |
Total Pages | : |
Release | : 1909 |
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Download Datensicherheit Book in PDF, Epub and Kindle
Author | : J. Sethuraman |
Publisher | : |
Total Pages | : 154 |
Release | : 1965 |
Genre | : Limit theorems (Probability theory) |
ISBN | : |
Download Limit Theorems for Stochastic Processes Book in PDF, Epub and Kindle
Author | : Ward Whitt |
Publisher | : Springer Science & Business Media |
Total Pages | : 616 |
Release | : 2006-04-11 |
Genre | : Mathematics |
ISBN | : 0387217487 |
Download Stochastic-Process Limits Book in PDF, Epub and Kindle
From the reviews: "The material is self-contained, but it is technical and a solid foundation in probability and queuing theory is beneficial to prospective readers. [... It] is intended to be accessible to those with less background. This book is a must to researchers and graduate students interested in these areas." ISI Short Book Reviews
Author | : D. Pollard |
Publisher | : David Pollard |
Total Pages | : 223 |
Release | : 1984-10-08 |
Genre | : Mathematics |
ISBN | : 0387909907 |
Download Convergence of Stochastic Processes Book in PDF, Epub and Kindle
Functionals on stochastic processes; Uniform convergence of empirical measures; Convergence in distribution in euclidean spaces; Convergence in distribution in metric spaces; The uniform metric on space of cadlag functions; The skorohod metric on D [0, oo); Central limit teorems; Martingales.
Author | : Vidyadhar S. Mandrekar |
Publisher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 148 |
Release | : 2016-09-26 |
Genre | : Mathematics |
ISBN | : 3110476312 |
Download Weak Convergence of Stochastic Processes Book in PDF, Epub and Kindle
The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents: Weak convergence of stochastic processes Weak convergence in metric spaces Weak convergence on C[0, 1] and D[0,∞) Central limit theorem for semi-martingales and applications Central limit theorems for dependent random variables Empirical process Bibliography
Author | : A.D. Wentzell |
Publisher | : Springer Science & Business Media |
Total Pages | : 192 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 9400918526 |
Download Limit Theorems on Large Deviations for Markov Stochastic Processes Book in PDF, Epub and Kindle
In recent decades a new branch of probability theory has been developing intensively, namely, limit theorems for stochastic processes. As compared to classical limit theorems for sums of independent random variables, the generalizations are going here in two directions simultaneously. First, instead of sums of independent variables one considers stochastic processes belonging to certain broad classes. Secondly, instead of the distribution of a single sum - the distribution of the value of a stochastic process at one (time) point - or the joint distribution of the values of a process at a finite number of points, one considers distributions in an infinite-dimensional function space. For stochastic processes constructed, starting from sums of independent random variables, this is the same as considering the joint distribution of an unboundedly increasing number of sums.
Author | : Hubert Hennion |
Publisher | : Springer Science & Business Media |
Total Pages | : 150 |
Release | : 2001-08 |
Genre | : Mathematics |
ISBN | : 3540424156 |
Download Limit Theorems for Markov Chains and Stochastic Properties of Dynamical Systems by Quasi-Compactness Book in PDF, Epub and Kindle
This book shows how techniques from the perturbation theory of operators, applied to a quasi-compact positive kernel, may be used to obtain limit theorems for Markov chains or to describe stochastic properties of dynamical systems. A general framework for this method is given and then applied to treat several specific cases. An essential element of this work is the description of the peripheral spectra of a quasi-compact Markov kernel and of its Fourier-Laplace perturbations. This is first done in the ergodic but non-mixing case. This work is extended by the second author to the non-ergodic case. The only prerequisites for this book are a knowledge of the basic techniques of probability theory and of notions of elementary functional analysis.