Vidyadhar S. Mandrekar – författare

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11 produkter

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11 produkter

Weakly Stationary Random Fields, Invariant Subspaces and Applications
AvVidyadhar S. Mandrekar,David A. Redett
Häftad, Engelska, 2020
776 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
776 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
906 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
2 683 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
915 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
908 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
1 786 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
906 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
878 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
1 008 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
1 008 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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