Handbook of the Normal Distribution, Second Edition PDF Download
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Author: Jagdish K. Patel
Publisher: CRC Press
ISBN: 9780824793425
Category : Mathematics
Languages : en
Pages : 452
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Book Description
"Traces the historical development of the normal law. Second Edition offers a comprehensive treatment of the bivariate normal distribution--presenting entirely new material on normal integrals, asymptotic normality, the asymptotic properties of order statistics, and point estimation and statistical intervals."
Author: Jagdish K. Patel
Publisher: CRC Press
ISBN: 9780824793425
Category : Mathematics
Languages : en
Pages : 452
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Book Description
"Traces the historical development of the normal law. Second Edition offers a comprehensive treatment of the bivariate normal distribution--presenting entirely new material on normal integrals, asymptotic normality, the asymptotic properties of order statistics, and point estimation and statistical intervals."
Author: Jagdish K. Patel
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 360
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Book Description
A collection of results relating to the normal distribution, tracing the historical development of normal law and providing a compendium of properties. The revised edition introduces the most current estimation procedures for normally distributed samples for researchers and students in theoretical and applied statistics, including expanded treatments of: bivariate normal distribution, normal integrals, Mills' ratio, asymptotic normality, point estimation, and statistical intervals. Annotation copyright by Book News, Inc., Portland, OR
Author: K. Krishnamoorthy
Publisher: CRC Press
ISBN: 1498741509
Category : Mathematics
Languages : en
Pages : 423
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Book Description
Easy-to-Use Reference and Software for Statistical Modeling and TestingHandbook of Statistical Distributions with Applications, Second Edition provides quick access to common and specialized probability distributions for modeling practical problems and performing statistical calculations. Along with many new examples and results, this edition inclu
Author: Nabendu Pal
Publisher: CRC Press
ISBN: 0203490282
Category : Mathematics
Languages : en
Pages : 370
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Book Description
The normal distribution is widely known and used by scientists and engineers. However, there are many cases when the normal distribution is not appropriate, due to the data being skewed. Rather than leaving you to search through journal articles, advanced theoretical monographs, or introductory texts for alternative distributions, the Handbook of E
Author: Wlodzimierz Bryc
Publisher: Springer Science & Business Media
ISBN: 1461225604
Category : Mathematics
Languages : en
Pages : 142
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Book Description
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.
Author: Mohammad Ahsanullah
Publisher: Springer Science & Business Media
ISBN: 9462390614
Category : Mathematics
Languages : en
Pages : 163
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Book Description
The most important properties of normal and Student t-distributions are presented. A number of applications of these properties are demonstrated. New related results dealing with the distributions of the sum, product and ratio of the independent normal and Student distributions are presented. The materials will be useful to the advanced undergraduate and graduate students and practitioners in the various fields of science and engineering.
Author: Nick T. Thomopoulos
Publisher: Springer
ISBN: 3319651129
Category : Mathematics
Languages : en
Pages : 176
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Book Description
This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines. The informed researcher will select the statistical distribution that best fits the data in the study at hand. Some of the distributions are well known to the general researcher and are in use in a wide variety of ways. Other useful distributions are less understood and are not in common use. The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study. The distributions are for continuous, discrete, and bivariate random variables. In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values. In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of the parameter values to be gained. This handbook of statistical distributions provides a working knowledge of applying common and uncommon statistical distributions in research studies. These nineteen distributions are: continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, left-truncated normal, right-truncated normal, triangular, discrete uniform, binomial, geometric, Pascal, Poisson, hyper-geometric, bivariate normal, and bivariate lognormal. Some are from continuous data and others are from discrete and bivariate data. This group of statistical distributions has ample application to studies in statistics and probability and practical use in real situations. Additionally, this book explains computing the cumulative probability of each distribution and estimating the parameter values either with sample data or without sample data. Examples are provided throughout to guide the reader. Accuracy in choosing and applying statistical distributions is particularly imperative for anyone who does statistical and probability analysis, including management scientists, market researchers, engineers, mathematicians, physicists, chemists, economists, social science researchers, and students in many disciplines.
Author: Henry C. Thode
Publisher: CRC Press
ISBN: 9780203910894
Category : Mathematics
Languages : en
Pages : 506
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Book Description
Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and multivariate normality. Contains tests ofr multivariate normality and coordinate-dependent and invariant approaches.
Author: Frank A. Haight
Publisher:
ISBN:
Category : Poisson distribution
Languages : en
Pages : 192
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Book Description
Author: Vijay Singh
Publisher: Springer Science & Business Media
ISBN: 9780792352242
Category : Science
Languages : en
Pages : 400
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Book Description
Since the pioneering work of Shannon in the late 1940's on the development of the theory of entropy and the landmark contributions of Jaynes a decade later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design, ecology, economics, environmental engineering, earth sciences, fluid mechanics, genetics, geology, geomorphology, geophysics, geotechnical engineering, hydraulics, hydrology, image processing, management sciences, operations research, pattern recognition and identification, photogrammetry, psychology, physics and quantum mechanics, reliability analysis, reservoir engineering, statistical mechanics, thermodynamics, topology, transportation engineering, turbulence modeling, and so on. New areas finding application of entropy have since continued to unfold. The entropy concept is indeed versatile and its applicability widespread. In the area of hydrology and water resources, a range of applications of entropy have been reported during the past three decades or so. This book focuses on parameter estimation using entropy for a number of distributions frequently used in hydrology. In the entropy-based parameter estimation the distribution parameters are expressed in terms of the given information, called constraints. Thus, the method lends itself to a physical interpretation of the parameters. Because the information to be specified usually constitutes sufficient statistics for the distribution under consideration, the entropy method provides a quantitative way to express the information contained in the distribution.
