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Stochastic Analysis for Gaussian Random Processes and Fields

singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian;

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Stochastic Analysis for Gaussian Random Processes and Fields

of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Gaussian Markov Random Fields

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to;

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Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

This book discusses the theory, method and application of non-Gaussian random vibration fatigue analysis and test. The main contents;

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Gaussian and Non-Gaussian Linear Time Series and Random Fields

The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical;

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Markov Processes, Gaussian Processes, and Local Times

properties of Markov processes by using well-established techniques in Gaussian process theory. This original, readable book will appeal to both;

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Markov Processes, Gaussian Processes, and Local Times

be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original;

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Visual Analysis of Behaviour

, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields;

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Level Sets and Extrema of Random Processes and Fields

. Level Sets and Extrema of Random Processes and Fields is an excellent book for courses on probability theory, spatial statistics, Gaussian;

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Random Fields for Spatial Data Modeling

field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model;

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Weakly Stationary Random Fields, Invariant Subspaces and Applications

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with;

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Weakly Stationary Random Fields, Invariant Subspaces and Applications

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with;

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Probability

limiting theorems, Bayesian computational methods, as well as a modern view on sampling and reconstruction of Gaussian and non-Gaussian random;

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Stable Non-Gaussian Random Processes

This book presents similarity between Gaussian and non-Gaussian stable multivariate distributions and introduces the one-dimensional stable;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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Random Motions in Markov and SemiMarkov Random Environments 2

This book is the second of two volumes on random motions in Markov and semi-Markov random environments. This second volume focuses on high;

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Topological Complexity of Smooth Random Functions

statistical applications. The notes include an introduction to the general theory of Gaussian random fields, treating classical topics such as;

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Random Fields Estimation

This book contains a novel theory of random fields estimation of Wiener type, developed originally by the author and presented here. No;

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Markov Semigroups at Saint-Flour

Bakry, Dominique: Hypercontractivity and its Usage in Semigroup Theory.- Ledoux, Michel: Isoperimetry and Gaussian Analysis.- Saloff-Coste;

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Statistical Inference in Financial and Insurance Mathematics with R

with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described;

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Asymptotic Properties of Permanental Sequences

density of a transient Markov process. When the Markov process is symmetric, a 1/2-permanental process is the square of a Gaussian process;

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Hybrid Random Fields

of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these;

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Stochastic Analysis & Applications

Increments of a Class of Gaussian Processes; Random Walk Tests & Pseudorandom Number Generators; Increments Theory on Gaussian Processes; The Law;

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Markov Random Field Modeling in Image Analysis

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables;

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Simulation of Stochastic Processes with Given Accuracy and Reliability

reliability in functional spaces. The authors explore analysis of the theory of Sub-Gaussian (including Gaussian one) and Square Gaussian random;

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