Cover of: The inverse Gaussian distribution | Raj S. Chhikara

The inverse Gaussian distribution

theory, methodology, and applications
  • 213 Pages
  • 1.84 MB
  • 8887 Downloads
  • English
by
M. Dekker , New York
Inverse Gaussian distribu
StatementRaj S. Chhikara, J. Leroy Folks.
SeriesStatistics, textbooks and monographs ;, v. 95
ContributionsFolks, Leroy, 1929-
Classifications
LC ClassificationsQA276.7 .C48 1989
The Physical Object
Paginationviii, 213 p. :
ID Numbers
Open LibraryOL2043430M
ISBN 100824779975
LC Control Number88020271

This book provides a comprehensive and penetrating account of the inverse Gaussian law. Beginning with an exhaustive historical overview that presents--for the first time--Etienne Halphen's pioneering wartime contributions, the book proceeds to a rigorous exposition of the theory of exponential families, focusing in particular on the inverse Gaussian law.

The inverse Gaussian distribution, its properties, and its implications are set in a wide perspective. The concepts of inversion and inverse natural exponential functions are presented, together with an analysis of the `Tweedie' scale, of which the Gaussian distribution is an important special : V.

Seshadri. The inverse Gaussian is a skew ed, two-parameter continuous distribution whose density is sim- ilar to the Gamma distribution with greater skewness and a sharper peak.

The distribution de. This book is written in the hope that it will serve as a companion volume to my first monograph. The first monograph was largely devoted to the probabilistic aspects of the inverse Gaussian law and therefore ignored the statistical issues and related data : Asit P.

Basu. The Inverse Gaussian Distribution: Theory: Methodology, and Applications (Statistics: A Series of Textbooks and Monographs) by Raj Chhikara and a great selection of related books, art and collectibles available now at This book provides a comprehensive and penetrating account of the inverse Gaussian law.

Beginning The inverse Gaussian distribution book an exhaustive historical overview that presents—for the first time—Etienne Halphen's pioneering wartime contributions, The inverse Gaussian distribution book book proceeds to a rigorous exposition of the theory of exponential families, focusing in particular on the inverse Gaussian : $ This book is written in the hope that it will serve as a companion volume to my first monograph.

The first monograph was largely devoted to the probabilistic aspects of the inverse Gaussian law and therefore ignored the statistical issues and related Brand: Springer-Verlag New York.

Book Description. This monograph is a compilation of research on the inverse Gaussian distribution. It emphasizes the presentation of the statistical properties, methods, and applications of the two-parameter inverse Gaussian family of distribution. It is useful to statisticians and users of statistical distribution.

The Inverse Gaussian Distribution: Theory: Methodology, and Applications (Statistics: A Series of Textbooks and Monographs) 1st Edition by Raj Chhikara (Author) ISBN ISBN Why is ISBN important. ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book.

Cited by: This book is written in the hope that it will serve as a companion volume to my first monograph. The first monograph was largely devoted to the probabilistic aspects of the inverse Gaussian law and therefore ignored the statistical issues and related data analyses.

Statistical Properties of the Generalized Inverse Gaussian Distribution (Lecture Notes in Statistics 9) by Bent Jorgensen and a great selection of related books, art.

Details The inverse Gaussian distribution EPUB

Inverse Gaussian Distribution. Also known as the Wald distribution, the inverse Gaussian is used to model nonnegative positively skewed data. "This book provides a comprehensive and penetrating account of the inverse Gaussian law. Beginning with an exhaustive historical overview that presents--for the first time--Etienne Halphen's pioneering wartime contributions, the book proceeds to a rigorous exposition of the theory of exponential families, focusing in particular on the inverse Gaussian law.

This monograph is a compilation of research on the inverse Gaussian distribution. It emphasizes the presentation of the statistical properties, methods, and applications of the two-parameter inverse Gaussian family of distribution.

It is useful to statisticians and users of 5/5(2). Chhikara RS, Folks JL () The inverse Gaussian distribution. Marcel Dekker, New York zbMATH Google Scholar Johnson NL, Kotz S, Balakrishnan N () Continuous univariate distributions, vol 1, 2nd edn.

InverseGaussianDistribution [μ, λ, θ] represents a continuous statistical distribution defined over the interval and parametrized by a real number θ (called an "index parameter") and by two positive real numbers μ (the mean of the distribution) and λ (called a "scale parameter").

Description The inverse Gaussian distribution PDF

Overall, the probability density function (PDF) of an inverse Gaussian distribution is unimodal with a. The Inverse Gaussian Distribution: Theory: Methodology, and Applications - CRC Press Book This monograph is a compilation of research on the inverse Gaussian distribution.

It emphasizes the presentation of the statistical properties, methods, and applications of the two-parameter inverse Gaussian family of distribution. This is related to the canonical form or JKB “two-parameter” inverse Gaussian when written in it’s full form with scale parameter \(S\) and location parameter \(L\) by taking \(L=0\) and \(S\equiv\lambda,\) then \(\mu S\) is equal to \(\mu_{2}\) where \(\mu_{2}\) is the parameter used by JKB.

We prefer this form because of it’s consistent use of the scale. inverse Gaussian distribution with parameters λand µ. An inverse Gaussian random variable X with parameters λand µ has probability density function f(x)= r λ 2πx3 e −λ(x−µ)2 2xµ2 x >0, for λ>0 and µ >0.

The inverse Gaussian distribution can be used to model the lifetime of an ob-ject. Stack Exchange network consists of Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange. Genre/Form: Handbooks and manuals Handbooks, manuals, etc: Additional Physical Format: Online version: CRC handbook of percentage points of the Inverse Gaussian distribution.

$\begingroup$ @harry The answer is readily available at wikipedia: wiki/Inverse_Gaussian_distribution $\endgroup$ – Sasha Sep 13 '13 at $\begingroup$ @StefanHansen My examination is knocking at the door $\endgroup$ – ABC Sep 13 '13 at Maleki M, Wraith D and Arellano-Valle R () Robust finite mixture modeling of multivariate unrestricted skew-normal generalized hyperbolic distributions, Statistics and Computing,(), Online publication date: 1-May For testing the fit of the inverse Gaussian distribution with unknown parameters, the empirical distribution-function statistic A2 is studied.

Download The inverse Gaussian distribution EPUB

On the Distribution of the Two-Sample Cramer-von Mises Criterion Anderson, T. W., The Annals of Mathematical Statistics, ; Statistical Properties of Inverse Gaussian Distributions.

II Tweedie, M. K., The Annals of Mathematical Statistics, ; A Characterization of the Inverse Gaussian Distribution Khatri, C. G., The Annals of. pleted by assigning a distribution forν i. If we assign gamma distribution for ν i, the resulting marginal density of Y i is the negative binomial (see, Collings and Margolin and McCullagh and Nelder ).

Alternatively, we assume that ν i has an inverse-Gaussian distribution, parameterized to have E(ν i)=1and var(ν i)=λ>0 so that. Computer algorithms are described for simulation of the generalized inverse Gaussian, generalized hyperbolic and hyperbolic distributions.

The efficiencies of the algorithms are found. Timing comparisons with the best available algorithms for sampling the gamma distribution show the new algorithms to be acceptably fast.

The extension to sampling multivariate generalized Cited by: The inverse Gaussian (Wald) distribution has applications in the study of diffusion processes and as a lifetime distribution model. This chapter illustrates the probability density function for the I: 1, λ variate for selected values of the scale parameter λ.

The purpose of this handbook is to provide comprehensive tables of percentage points of the inverse Gaussian distribution. There is no other publication available today which condenses these tables - to such extent-in a concise, straightforward manner.

The inverse Gaussian distribution is not only i. The standardized inverse Gaussian distribution, unlike the gamma and the Weibull distributions, does not become reverse J-shaped and retains the bell shape with a discernible mode for all values of the shape parameter k.

In this respect, it resembles the lognormal distribution more than either the Weibull or the gamma : N. Balakrishnan. MathWorld Book. Wolfram Web Resources» Inverse Gaussian Distribution.

The inverse Gaussian distribution, also known as the Wald distribution, is the distribution over with probability density function and distribution function given by (1) .The inverse Gaussian distribution: theory, methodology, and applications (Statistique), Inverse Gaussian distribution, Gauss, distribution de, Distribución (Teoría de la probabilidad), Inverse Normalverteilung, Estadística matemática, Statistique descriptive, Distribucion Borrow this book to access EPUB and PDF files.

IN COLLECTIONS.to purchase the book. Inverse Normal distribution: in the Natural Exponential Family This is a video demonstration of how to show that the Inverse Normal (Inverse Gaussian) distribution is a member of the natural Inverse Normal Distributions - How it all Works The inverse normal distribution function allows us to calculate the Page 1/5.