Probability Distributions Involving Gaussian Random Variables

Probability Distributions Involving Gaussian Random Variables

Author: Marvin K. Simon

Publisher: Springer Science & Business Media

Published: 2007-05-24

Total Pages: 218

ISBN-13: 0387476946

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This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.


Probability Distributions Involving Gaussian Random Variables

Probability Distributions Involving Gaussian Random Variables

Author: Marvin K. Simon

Publisher: Springer

Published: 2006-11-09

Total Pages: 200

ISBN-13: 9780387346571

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This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.


Probability Distributions Involving Gaussian Random Variables

Probability Distributions Involving Gaussian Random Variables

Author: Marvin K. Simon

Publisher: Springer

Published: 2008-11-01

Total Pages: 0

ISBN-13: 9780387514451

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This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.


Probability Distributions Used in Reliability Engineering

Probability Distributions Used in Reliability Engineering

Author: Andrew N O'Connor

Publisher: RIAC

Published: 2011

Total Pages: 220

ISBN-13: 1933904062

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The book provides details on 22 probability distributions. Each distribution section provides a graphical visualization and formulas for distribution parameters, along with distribution formulas. Common statistics such as moments and percentile formulas are followed by likelihood functions and in many cases the derivation of maximum likelihood estimates. Bayesian non-informative and conjugate priors are provided followed by a discussion on the distribution characteristics and applications in reliability engineering.


High-Dimensional Probability

High-Dimensional Probability

Author: Roman Vershynin

Publisher: Cambridge University Press

Published: 2018-09-27

Total Pages: 299

ISBN-13: 1108415199

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An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.


The Normal Distribution

The Normal Distribution

Author: Wlodzimierz Bryc

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 142

ISBN-13: 1461225604

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This book is a concise presentation of the normal distribution on the real line and its counterparts on more abstract spaces, which we shall call the Gaussian distributions. The material is selected towards presenting characteristic properties, or characterizations, of the normal distribution. There are many such properties and there are numerous rel evant works in the literature. In this book special attention is given to characterizations generated by the so called Maxwell's Theorem of statistical mechanics, which is stated in the introduction as Theorem 0.0.1. These characterizations are of interest both intrin sically, and as techniques that are worth being aware of. The book may also serve as a good introduction to diverse analytic methods of probability theory. We use characteristic functions, tail estimates, and occasionally dive into complex analysis. In the book we also show how the characteristic properties can be used to prove important results about the Gaussian processes and the abstract Gaussian vectors. For instance, in Section 5.4 we present Fernique's beautiful proofs of the zero-one law and of the integrability of abstract Gaussian vectors. The central limit theorem is obtained via characterizations in Section 7.3.


Continuous Multivariate Distributions, Volume 1

Continuous Multivariate Distributions, Volume 1

Author: Samuel Kotz

Publisher: John Wiley & Sons

Published: 2004-04-05

Total Pages: 752

ISBN-13: 0471654035

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Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications.


Statistics Using Technology, Second Edition

Statistics Using Technology, Second Edition

Author: Kathryn Kozak

Publisher: Lulu.com

Published: 2015-12-12

Total Pages: 459

ISBN-13: 1329757254

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Statistics With Technology, Second Edition, is an introductory statistics textbook. It uses the TI-83/84 calculator and R, an open source statistical software, for all calculations. Other technology can also be used besides the TI-83/84 calculator and the software R, but these are the ones that are presented in the text. This book presents probability and statistics from a more conceptual approach, and focuses less on computation. Analysis and interpretation of data is more important than how to compute basic statistical values.


Introduction to Probability

Introduction to Probability

Author: David F. Anderson

Publisher: Cambridge University Press

Published: 2017-11-02

Total Pages: 447

ISBN-13: 110824498X

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This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.


Probability-Based Structural Fire Load

Probability-Based Structural Fire Load

Author: Leo Razdolsky

Publisher: Cambridge University Press

Published: 2014-08-25

Total Pages: 353

ISBN-13: 110703874X

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This book introduces the subject of probabilistic analysis to engineers and can be used as a reference in applying this technology.