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A Course in Large Sample Theory

A Course in Large Sample Theory is presented in four parts. The first treats basic probabilistic notions, the second features the basic;

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A Course in Large Sample Theory

A Course in Large Sample Theory is presented in four parts. The first treats basic probabilistic notions, the second features the basic;

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Course in Mathematical Statistics and Large Sample Theory

undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a;

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Large Sample Techniques for Statistics

new edition introduces a final chapter dedicated to random matrix theory, as well as expanded treatment of inequalities and mixed effects;

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Elements of Large-Sample Theory

theory. It discusses a broad range of applications including introductions to density estimation, the bootstrap, and the asymptotics of survey;

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Large Sample Methods in Statistics (1994)

standard symptotic statistical methods. It contains a unified survey of standard large sample theory and provides access to more complex;

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Asymptotic Theory Of Statistics And Prob

This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical;

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Asymptotic Theory of Statistics and Probability

This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical;

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Theory Of Sample Surveys

students, a prerequisite basic knowledge of algebra, calculus, and statistical theory is required to master the techniques described in this book.;

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Introduction to Probability and Statistics

; multivariate distributions; large-sample methods; decision theory; and applications of ANOVA.;A primary text for a year-long undergraduate course;

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Introduction to Probability and Statistics

; multivariate distributions; large-sample methods; decision theory; and applications of ANOVA.;A primary text for a year-long undergraduate course;

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Theory of Statistical Inference

Theory of Statistical Inference is designed as a reference on statistical inference for researchers and students at the graduate or;

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A First Course in Random Matrix Theory

theory and the study of large sample covariance matrices can efficiently process these big data sets and help make sense of modern, deep learning;

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An Introduction to Multiagent Systems

. Assuming only a basic understanding of computer science, this text provides an introduction to all the main issues in the theory and practice;

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Robust Multivariate Analysis

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain;

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Statistical Theory and Inference

This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum;

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A Course on Large Deviations with an Introduction to Gibbs Measures

This is an introductory course on the methods of computing asymptotics of probabilities of rare events: the theory of large deviations. The;

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Exact Analysis of Discrete Data

large sample methods. When sample sizes are not large or the data are otherwise sparse, exact methods--methods not based on asymptotic theory;

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The Training Design Manual

chapters contains elements of theory interleaved with practical exercises that build towards the design of a complete course. Topics include (for;

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A First Course in Information Theory

comprehensive treatment of the theory of I-Measure, network coding theory, Shannon and non-Shannon type information inequalities, and a relation between;

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Organization Theory

The SAGE Course Companion on Organization Theory is an accessible introduction to a challenging subject area. This book helps readers to;

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Organization Theory

The SAGE Course Companion on Organization Theory is an accessible introduction to a challenging subject area. This book helps readers to;

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Spectral Theory Of Large Dimensional Random Matrices And Its Applications To Wireless Communications And Finance Statistics

The book contains three parts: Spectral theory of large dimensional random matrices; Applications to wireless communications; and;

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Introduction To Statistical Time Series

. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new;

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Econometrics

Econometrics 2nd edition is designed as a complete text in econometric methods for intermediate and advanced undergraduates. The text;

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A Graduate Course on Statistical Inference

in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The;

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Large Deviations

The theory of large deviations deals with rates at which probabilities of certain events decay as a natural parameter in the problem varies;

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