The Exponential Family Generated by the Skew-normal Distribution PDF Download
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Author: Alessandra Dalla_Valle
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Author: Alessandra Dalla_Valle
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Author: Adelchi Azzalini
Publisher: Cambridge University Press
ISBN: 1107029279
Category : Business & Economics
Languages : en
Pages : 271
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Book Description
The standard resource for statisticians and applied researchers. Accessible to the wide range of researchers who use statistical modelling techniques.
Author: Allan R. Sampson
Publisher:
ISBN:
Category :
Languages : en
Pages : 16
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Book Description
It is shown that if T bar has an unknown exponential family distribution with natural parameter (theta bar), then (G bar) = ET uniquely specifies the moment generating function of T bar. Conversely, it is proved that if T bar is a random variable with a moment generating function of a prescribed form, then it has an exponential family distribution. These results are used to characterize the Normal, Poisson, Bernoulli and Wishart distributions, among others. (Author).
Author: Lawrence D. Brown
Publisher: IMS
ISBN: 9780940600102
Category : Business & Economics
Languages : en
Pages : 302
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Book Description
Author: Clécio da Silva Ferreira
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 32
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Book Description
Author: V. Seshadri
Publisher: Oxford University Press on Demand
ISBN: 9780198522430
Category : Mathematics
Languages : en
Pages : 256
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Book Description
This book begins with a historical survey of `generalized inverse Gaussian laws', in which the wartime contribution of Etienne Halphen is presented for the first time. 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 specialcase. Chapter 2 concerns the basic theory of exponential functions, focusing on the inverse Gaussian Law. Chapter 3 is devoted to various characterization results, while Chapter 4 is concerned with the construction of multivariate distributions, and the relationship to simplex distributions,combinations, and finite mixtures. Chapter 5 introduces the concept of inverse natural exponential functions and Chapter 6 presents useful statistical results. Up-to-date research is presented in the form of exercises, a special chapter on characterizations is included, and a summary of statistical issues concerning estimation and interference are provided. Research workers will find inspiration for further investigations.
Author: K. Balakrishnan
Publisher: Routledge
ISBN: 1351449125
Category : Mathematics
Languages : en
Pages : 664
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Book Description
The exponential distribution is one of the most significant and widely used distribution in statistical practice. It possesses several important statistical properties, and yet exhibits great mathematical tractability. This volume provides a systematic and comprehensive synthesis of the diverse literature on the theory and applications of the expon
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: Robert A. Rigby
Publisher: CRC Press
ISBN: 100069996X
Category : Mathematics
Languages : en
Pages : 589
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Book Description
This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application. Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness. Includes mixed distributions which are continuous distributions with additional specific values with point probabilities. Includes many real data examples, with R code integrated in the text for ease of understanding and replication. Supplemented by the gamlss website. This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.
Author: N. Balakrishnan
Publisher: CRC Press
ISBN: 9780849384844
Category : Mathematics
Languages : en
Pages : 630
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Book Description
This book highlights various theoretical developments on logistic distribution, illustrates the practical utility of these results, and describes univariate and multivariate generalizations of the distribution. It is useful for researchers, practicing statisticians, and graduate students.
