Vidyadhar S. Mandrekar – författare & böcker

Weakly Stationary Random Fields, Invariant Subspaces and Applications

AvVidyadhar S. Mandrekar,David A. Redett

Häftad, Engelska, 2020

726 kr

Skickas inom 10-15 vardagar

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.

Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

AvVidyadhar S. Mandrekar,Leszek Gawarecki

Häftad, Engelska, 2020

726 kr

Skickas inom 10-15 vardagar

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 before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the Itô integral. They show how the Skorokhod integral is a dual operator of Skorokhod differentiation and the divergence operator of Malliavin. The authors also present Gaussian processes indexed by real numbers and obtain a Kallianpur–Striebel Bayes' formula for the filtering problem. After discussing the problem of equivalence and singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields is connected to the Markov process generated by a Dirichlet form.

Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

AvLeszek Gawarecki,Vidyadhar S. Mandrekar

E-bok

Engelska, 2015

835 kr

Läs direkt efter köp

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

Weakly Stationary Random Fields, Invariant Subspaces and Applications

AvVidyadhar S. Mandrekar,David A. Redett

Inbunden, Engelska, 2017

2 394 kr

Skickas inom 10-15 vardagar

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.

Weakly Stationary Random Fields, Invariant Subspaces and Applications

AvDavid A. Redett,Vidyadhar S. Mandrekar

E-bok

Engelska, 2017

828 kr

Läs direkt efter köp

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.

Weakly Stationary Random Fields, Invariant Subspaces and Applications

AvDavid A. Redett,Vidyadhar S. Mandrekar

E-bok

PDF, Engelska, 2017

828 kr

Läs direkt efter köp

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.

Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

AvVidyadhar S. Mandrekar,Leszek Gawarecki

Inbunden, Engelska, 2015

1 481 kr

Skickas inom 10-15 vardagar

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 before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the Itô integral. They show how the Skorokhod integral is a dual operator of Skorokhod differentiation and the divergence operator of Malliavin. The authors also present Gaussian processes indexed by real numbers and obtain a Kallianpur–Striebel Bayes' formula for the filtering problem. After discussing the problem of equivalence and singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields is connected to the Markov process generated by a Dirichlet form.

Stochastic Analysis for Gaussian Random Processes and Fields

With Applications

AvLeszek Gawarecki,Vidyadhar S. Mandrekar

E-bok

PDF, Engelska, 2015

828 kr

Läs direkt efter köp

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

Weak Convergence of Stochastic Processes

With Applications to Statistical Limit Theorems

AvVidyadhar S. Mandrekar

Häftad, Engelska, 2016

880 kr

Skickas inom 5-8 vardagar

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 processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography

Weak Convergence of Stochastic Processes

With Applications to Statistical Limit Theorems

AvVidyadhar S. Mandrekar

E-bok

Engelska, 2016

1 011 kr

Läs direkt efter köp

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 processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography

Weak Convergence of Stochastic Processes

With Applications to Statistical Limit Theorems

AvVidyadhar S. Mandrekar

E-bok

PDF, Engelska, 2016

1 011 kr

Läs direkt efter köp

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 processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography

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Vidyadhar S. Mandrekar – författare

Weakly Stationary Random Fields, Invariant Subspaces and Applications

Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields

Weakly Stationary Random Fields, Invariant Subspaces and Applications

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

Weak Convergence of Stochastic Processes

Weak Convergence of Stochastic Processes

Weak Convergence of Stochastic Processes

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