Handbook of Fitting Statistical Distributions with R

Handbook of Fitting Statistical Distributions with R PDF Author: Zaven A. Karian
Publisher: Chapman and Hall/CRC
ISBN: 9781584887119
Category : Mathematics
Languages : en
Pages : 1718

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Book Description
With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods, algorithms, and computations for fitting distributions to data. It also provides in-depth coverage of cutting-edge applications. The book begins with commentary by three GLD pioneers: John S. Ramberg, Bruce Schmeiser, and Pandu R. Tadikamalla. These leaders of the field give their perspectives on the development of the GLD. The book then covers GLD methodology and Johnson, kappa, and response modeling methodology fitting systems. It also describes recent additions to GLD and generalized bootstrap methods as well as a new approach to goodness-of-fit assessment. The final group of chapters explores real-world applications in agriculture, reliability estimation, hurricanes/typhoons/cyclones, hail storms, water systems, insurance and inventory management, and materials science. The applications in these chapters complement others in the book that deal with competitive bidding, medicine, biology, meteorology, bioassays, economics, quality management, engineering, control, and planning. New results in the field have generated a rich array of methods for practitioners. Making sense of this extensive growth, this comprehensive and authoritative handbook improves your understanding of the methodology and applications of fitting statistical distributions. The accompanying CD-ROM includes the R programs used for many of the computations.

Handbook of Fitting Statistical Distributions with R

Handbook of Fitting Statistical Distributions with R PDF Author: Zaven A. Karian
Publisher: Chapman and Hall/CRC
ISBN: 9781584887119
Category : Mathematics
Languages : en
Pages : 1718

Get Book Here

Book Description
With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods, algorithms, and computations for fitting distributions to data. It also provides in-depth coverage of cutting-edge applications. The book begins with commentary by three GLD pioneers: John S. Ramberg, Bruce Schmeiser, and Pandu R. Tadikamalla. These leaders of the field give their perspectives on the development of the GLD. The book then covers GLD methodology and Johnson, kappa, and response modeling methodology fitting systems. It also describes recent additions to GLD and generalized bootstrap methods as well as a new approach to goodness-of-fit assessment. The final group of chapters explores real-world applications in agriculture, reliability estimation, hurricanes/typhoons/cyclones, hail storms, water systems, insurance and inventory management, and materials science. The applications in these chapters complement others in the book that deal with competitive bidding, medicine, biology, meteorology, bioassays, economics, quality management, engineering, control, and planning. New results in the field have generated a rich array of methods for practitioners. Making sense of this extensive growth, this comprehensive and authoritative handbook improves your understanding of the methodology and applications of fitting statistical distributions. The accompanying CD-ROM includes the R programs used for many of the computations.

Fitting Statistical Distributions

Fitting Statistical Distributions PDF Author: Zaven A. Karian
Publisher: CRC Press
ISBN: 1420038044
Category : Mathematics
Languages : en
Pages : 458

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Book Description
Although the study of statistical modelling has made great strides in recent years, the number and variety of distributions to choose from continue to create problems. . Focusing on techniques used successfully across many fields, Fitting Statistical Distributions presents all of the relevant results related to the Generalized Lambda Distribution, the Generalized Bootstrap, and Monte Carlo simulation. It provides the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a wide variety of circumstances-covering bivariate as well as univariate distributions, and including situations where moments do not exist.

IPython Interactive Computing and Visualization Cookbook

IPython Interactive Computing and Visualization Cookbook PDF Author: Cyrille Rossant
Publisher: Packt Publishing Ltd
ISBN: 178328482X
Category : Computers
Languages : en
Pages : 899

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Book Description
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Handbook of Fitting Statistical Distributions with R

Handbook of Fitting Statistical Distributions with R PDF Author: Zaven A. Karian
Publisher: CRC Press
ISBN: 1584887125
Category : Mathematics
Languages : en
Pages : 1722

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Book Description
With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods

Statistical Distributions

Statistical Distributions PDF Author: Catherine Forbes
Publisher: John Wiley & Sons
ISBN: 1118097823
Category : Mathematics
Languages : en
Pages : 206

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Book Description
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with related facts and formulas. Reflecting the latest changes and trends in statistical distribution theory, the Fourth Edition features: A new chapter on queuing formulas that discusses standard formulas that often arise from simple queuing systems Methods for extending independent modeling schemes to the dependent case, covering techniques for generating complex distributions from simple distributions New coverage of conditional probability, including conditional expectations and joint and marginal distributions Commonly used tables associated with the normal (Gaussian), student-t, F and chi-square distributions Additional reviewing methods for the estimation of unknown parameters, such as the method of percentiles, the method of moments, maximum likelihood inference, and Bayesian inference Statistical Distributions, Fourth Edition is an excellent supplement for upper-undergraduate and graduate level courses on the topic. It is also a valuable reference for researchers and practitioners in the fields of engineering, economics, operations research, and the social sciences who conduct statistical analyses.

Probability Distributions Used in Reliability Engineering

Probability Distributions Used in Reliability Engineering PDF Author: Andrew N O'Connor
Publisher: RIAC
ISBN: 1933904062
Category : Mathematics
Languages : en
Pages : 220

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Book Description
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.

Normal and Student ́s t Distributions and Their Applications

Normal and Student ́s t Distributions and Their Applications PDF 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.

Loss Distributions

Loss Distributions PDF Author: Robert V. Hogg
Publisher: John Wiley & Sons
ISBN: 0470317302
Category : Business & Economics
Languages : en
Pages : 254

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Book Description
Devoted to the problem of fitting parametric probability distributions to data, this treatment uniquely unifies loss modeling in one book. Data sets used are related to the insurance industry, but can be applied to other distributions. Emphasis is on the distribution of single losses related to claims made against various types of insurance policies. Includes five sets of insurance data as examples.

Goodness-of-Fit-Techniques

Goodness-of-Fit-Techniques PDF Author: RalphB. D'Agostino
Publisher: Routledge
ISBN: 1351444565
Category : Mathematics
Languages : en
Pages : 585

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Book Description
Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction , and also collecting methods of testing for specific famous distributions, this usefulreference is the fust comprehensive.review of the extensive literature on the subject. It surveysthe leading methods of testing fit . .. provides tables to make the tests available . .. assessesthe comparative merits of different test procedures . .. and supplies numerical examples to aidin understanding these techniques.Goodness-of-Fit Techniques shows how to apply the techniques . .. emphasizes testing for thethree major distributions, normal, exponential, and uniform . .. discusses the handling of censoreddata .. . and contains over 650 bibliographic citations that cover the field.Illustrated with tables and drawings, this volume is an ideal reference for mathematical andapplied statisticians, and biostatisticians; professionals in applied science fields, including psychologists,biometricians , physicians, and quality control and reliability engineers; advancedundergraduate- and graduate-level courses on goodness-of-fit techniques; and professional seminarsand symposia on applied statistics, quality control, and reliability.

Continuous Univariate Distributions, Volume 2

Continuous Univariate Distributions, Volume 2 PDF Author: Norman L. Johnson
Publisher: John Wiley & Sons
ISBN: 0471584940
Category : Mathematics
Languages : en
Pages : 747

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Book Description
Comprehensive reference for statistical distributions Continuous Univariate Distributions, Volume 2 provides in-depth reference for anyone who applies statistical distributions in fields including engineering, business, economics, and the sciences. Covering a range of distributions, both common and uncommon, this book includes guidance toward extreme value, logistics, Laplace, beta, rectangular, noncentral distributions and more. Each distribution is presented individually for ease of reference, with clear explanations of methods of inference, tolerance limits, applications, characterizations, and other important aspects, including reference to other related distributions.