Vidyadhar S. Mandrekar's Books

Weak Convergence of Stochastic Processes

With Applications to Statistical Limit Theorems

By: Vidyadhar S. Mandrekar

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Weak Convergence of Stochastic Processes

With Applications to Statistical Limit Theorems

By: Vidyadhar S. Mandrekar

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

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Page Count

148

Publisher

Walter de Gruyter GmbH & Co KG

Published Date

ISBN 10

3110476312

ISBN 13

9783110476316

Weakly Stationary Random Fields, Invariant Subspaces and Applications

By: Vidyadhar S. Mandrekar,David A. Redett

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Weakly Stationary Random Fields, Invariant Subspaces and Applications

By: Vidyadhar S. Mandrekar,David A. Redett

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with functional analysis). It reviews current literature, presents central issues and most important results within the area. For advanced Ph.D. students, researchers, especially those conducting research on Gaussian theory.

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Page Count

174

Publisher

CRC Press

Published Date

ISBN 10

1351356453

ISBN 13

9781351356459

Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

By: Vidyadhar S. Mandrekar,Leszek Gawarecki

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Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

By: Vidyadhar S. Mandrekar,Leszek Gawarecki

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).The book begins with preliminary results on covariance and associated RKHS

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Page Count

200

Publisher

CRC Press

Published Date

ISBN 10

1498707823

ISBN 13

9781498707824

Stochastic Integration in Banach Spaces

Theory and Applications

By: Vidyadhar Mandrekar,Barbara Rüdiger

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Stochastic Integration in Banach Spaces

Theory and Applications

By: Vidyadhar Mandrekar,Barbara Rüdiger

Considering Poisson random measures as the driving sources for stochastic (partial) differential equations allows us to incorporate jumps and to model sudden, unexpected phenomena. By using such equations the present book introduces a new method for modeling the states of complex systems perturbed by random sources over time, such as interest rates in financial markets or temperature distributions in a specific region. It studies properties of the solutions of the stochastic equations, observing the long-term behavior and the sensitivity of the solutions to changes in the initial data. The authors consider an integration theory of measurable and adapted processes in appropriate Banach spaces as well as the non-Gaussian case, whereas most of the literature only focuses on predictable settings in Hilbert spaces. The book is intended for graduate students and researchers in stochastic (partial) differential equations, mathematical finance and non-linear filtering and assumes a knowledge of the required integration theory, existence and uniqueness results and stability theory. The results will be of particular interest to natural scientists and the finance community. Readers should ideally be familiar with stochastic processes and probability theory in general, as well as functional analysis and in particular the theory of operator semigroups.

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Page Count

213

Publisher

Springer

Published Date

ISBN 10

3319128531

ISBN 13

9783319128535

Book's by Vidyadhar S. Mandrekar

Weak Convergence of Stochastic Processes

Weak Convergence of Stochastic Processes

Weakly Stationary Random Fields, Invariant Subspaces and Applications

Weakly Stationary Random Fields, Invariant Subspaces and Applications

Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Integration in Banach Spaces

Stochastic Integration in Banach Spaces

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