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Self-Normalized Processes: Limit Theory and Statistical Applications

Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t;

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Weak Convergence of Stochastic Processes

range of literature, are for the first time presented here in a self-contained fashion. Contents: Weak convergence of stochastic processes;

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London Mathematical Society Lecture Note Series

Hidden Markov processes (HMPs) are important objects of study in many areas of pure and applied mathematics, including information theory;

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Limit Distributions for Sums of Independent Random Vectors

central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory;

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Quantile Processes with Statistical Applications

Provides a comprehensive theory of the approximations of quantile processes in light of recent advances, as well as some of their;

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Introduction to Statistical Limit Theory

Helping students develop a good understanding of asymptotic theory, Introduction to Statistical Limit Theory provides a thorough yet;

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Introduction to Statistical Limit Theory

Helping students develop a good understanding of asymptotic theory, Introduction to Statistical Limit Theory provides a thorough yet;

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Stochastic Limit Theory

strong laws of large numbers; weak convergence; and central limit theorems for nonstationary and dependent processes. The functional central;

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Semimartingales and their Statistical Inference

semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory;

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Semimartingales and Their Statistical Inference

semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory;

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Towards Intelligent Modeling: Statistical Approximation Theory

limit fails. The results of this book not only cover the classical and statistical approximation theory, but also are applied in the fuzzy logic;

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Inference and Prediction in Large Dimensions

adaptive projection - with applications to tests of fit and prediction, and theory of linear processes in function spaces with applications to;

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Random Summation

, information properties of probability distributions, and asymptotic behavior of doubly stochastic Poisson processes. Random Summation: Limit Theorems;

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Random Summation

, information properties of probability distributions, and asymptotic behavior of doubly stochastic Poisson processes. Random Summation: Limit Theorems;

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Reproducing Kernel Hilbert Spaces in Probability and Statistics

more fruitful and promising applications, including statistical signal processing, nonparametric curve estimation, random measures, limit;

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Limit Theorems For Associated Random Fields And Related Systems

, percolation theory, statistical physics and reliability theory. Attention is paid not only to positive and negative associations introduced in the;

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Topics in stochastic processes

, Ito and Prohorov. Special attention is also paid to Levy processes. The lectures are basically self-contained and rely only on elementary;

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Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic;

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Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

, Statistics of Diffusions, Markov Processes and other Statistical Applications.;

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Selfsimilar Processes

noncentral limit theory, long-range dependence, and operator selfsimilarity are covered alongside statistical estimation, simulation, sample path;

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Extreme Value Methods with Applications to Finance

. In addition, the book covers: Extremes in samples of random size Methods of estimating extreme quantiles and tail probabilities Self;

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Linear Processes in Function Spaces

The main subject of this book is the estimation and forecasting of continuous time processes. It leads to a development of the theory;

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Stationary Stochastic Processes

Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind;

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Geographical Genetics (MPB-38)

relationships of spatial statistical measures of patterns to stochastic processes. It also develops the probability and distribution theory of various;

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Statistics for Long-Memory Processes

Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range;

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Statistical Inference in Stochastic Processes

Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and;

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An Introduction to Probability Theory and Its Applications, Volume 2

The classic text for understanding complex statistical probability An Introduction to Probability Theory and Its Applications offers;

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