Testing The Fit Of The Weibull Distribution To Grouped Data
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Testing The Fit Of The Weibull Distribution To Grouped Data
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Author : R. Swindell
language : en
Publisher:
Release Date : 1974
Testing The Fit Of The Weibull Distribution To Grouped Data written by R. Swindell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with categories.
Two And Three Parameter Weibull Goodness Of Fit Tests
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Author : James W. Evans
language : en
Publisher:
Release Date : 1989
Two And Three Parameter Weibull Goodness Of Fit Tests written by James W. Evans and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Mathematical statistics categories.
Chi Squared Goodness Of Fit Tests For Censored Data
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Author : Mikhail S. Nikulin
language : en
Publisher: John Wiley & Sons
Release Date : 2017-06-29
Chi Squared Goodness Of Fit Tests For Censored Data written by Mikhail S. Nikulin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with Mathematics categories.
This book is devoted to the problems of construction and application of chi-squared goodness-of-fit tests for complete and censored data. Classical chi-squared tests assume that unknown distribution parameters are estimated using grouped data, but in practice this assumption is often forgotten. In this book, we consider modified chi-squared tests, which do not suffer from such a drawback. The authors provide examples of chi-squared tests for various distributions widely used in practice, and also consider chi-squared tests for the parametric proportional hazards model and accelerated failure time model, which are widely used in reliability and survival analysis. Particular attention is paid to the choice of grouping intervals and simulations. This book covers recent innovations in the field as well as important results previously only published in Russian. Chi-squared tests are compared with other goodness-of-fit tests (such as the Cramer-von Mises-Smirnov, Anderson-Darling and Zhang tests) in terms of power when testing close competing hypotheses.
Testing Of Grouped Product For The Weibull Distribution Using Neutrosophic Statistics
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Author : Muhammad Aslam
language : en
Publisher: Infinite Study
Release Date :
Testing Of Grouped Product For The Weibull Distribution Using Neutrosophic Statistics written by Muhammad Aslam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Parts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables are precise. Therefore, the existing sudden death test plan can be applied if failure data/or parameters are imprecise, incomplete, and fuzzy.
Testing Of Grouped Product For Theweibull Distribution Using Neutrosophic Statistics
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Author : Muhammad Aslam
language : en
Publisher: Infinite Study
Release Date :
Testing Of Grouped Product For Theweibull Distribution Using Neutrosophic Statistics written by Muhammad Aslam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Parts manufacturers use sudden death testing to reduce the testing time of experiments. The sudden death testing plan in the literature can only be applied when all observations of failure time/parameters are crisp. In practice however, it is noted that not all measurements of continuous variables are precise. Therefore, the existing sudden death test plan can be applied if failure data/or parameters are imprecise, incomplete, and fuzzy.
A New Sequential Goodness Of Fit Test For The Three Parameter Weibull Distribution With Known Shape Parameter Value Based On Skewness And Q Statis G O F Test Statistics
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Author : Tibet Memis
language : en
Publisher:
Release Date : 1999-03-01
A New Sequential Goodness Of Fit Test For The Three Parameter Weibull Distribution With Known Shape Parameter Value Based On Skewness And Q Statis G O F Test Statistics written by Tibet Memis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-01 with categories.
Due to its flexibility, the Weibull distribution has very wide applicability in a lot of disciplines and is very prevalent in reliability theory. Thus, a lot of statistical tests that generally have a substantial degree of computional complexity have been developed to determine if the data at hand can be represented with this distribution. This research presents a new omnibus goodness-of-fit test (G.O.F.) that has less computational complexity than the existing tests for the three-parameter Weibull distribution using a sequential application of two individual tests, sample skewness and Q-Statistic. A Monte Carlo procedure has been employed to generate critical values for the skewness and Q-Statistic (G.O.F.) tests for various Weibull distributions with specified shape parameter values. Additionally, tables or charts of attained significance levels for the new sequential G.O.F. test procedure have been generated. Using the critical values and significance levels, a sequential G.O. F. test procedure can be used to determine if the given sample data agrees with a hypothesized Weibull distribution with known shape. A power study has been conducted against a variety of alternative hypotheses, and the results were compared with those obtained using conventional EDF type Cramer-von Mises, Ahderson-Darling and Kolmogorov-Smimov G.O.F tests, and the sequential procedure by Clough. Since the sequential test demonstrates better or equivalent power, it serves to significantly reduce the computational requirements for powerful G.O. F. testing.
The Weibull Distribution
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Author : Horst Rinne
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2008-11-20
The Weibull Distribution written by Horst Rinne and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-20 with Mathematics categories.
The Most Comprehensive Book on the Subject Chronicles the Development of the Weibull Distribution in Statistical Theory and Applied Statistics Exploring one of the most important distributions in statistics, The Weibull Distribution: A Handbook focuses on its origin, statistical properties, and related distributions. The book also presents various approaches to estimate the parameters of the Weibull distribution under all possible situations of sampling data as well as approaches to parameter and goodness-of-fit testing. Describes the Statistical Methods, Concepts, Theories, and Applications of This Distribution Compiling findings from dozens of scientific journals and hundreds of research papers, the author first gives a careful and thorough mathematical description of the Weibull distribution and all of its features. He then deals with Weibull analysis, using classical and Bayesian approaches along with graphical and linear maximum likelihood techniques to estimate the three Weibull parameters. The author also explores the inference of Weibull processes, Weibull parameter testing, and different types of goodness-of-fit tests and methods. Successfully Apply the Weibull Model By using inferential procedures for estimating, testing, forecasting, and simulating data, this self-contained, detailed handbook shows how to solve statistical life science and engineering problems.
A New Goodness Of Fit Test For The Weibull Distribution Based On Spacings
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Author : Mark C. Coppa
language : en
Publisher:
Release Date : 1993
A New Goodness Of Fit Test For The Weibull Distribution Based On Spacings written by Mark C. Coppa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
The critical values for a new goodness-of-fit test based on spacings are generated for the Weibull distribution when the shape parameter is known. The critical values are used for testing whether a set of observations follow a Weibull distribution when the scale and location parameters are unknown. A Monte Carlo simulation with 10,000 iterations is used to generate the critical values for sample sizes 5(5)35 at shape parameters k equal to 0.5(0.5)1.5 and for sample sizes 5(5)20 at shape parameters k = 2.0(1.0)4.0. A Monte Carlo power study of the Z* test statistic using 5000 iterations is accomplished using nine alternate distributions H sub A. The power is good to excellent when the null hypothesis Ho is from a skewed distribution(k 2.0). Power results at shape parameters k 2.0 are poor for all sample sizes considered. A comparison is made, at shape parameter 1.0, against the prominent competing goodness-of-fit test statistics. Data is obtained from a prior AFIT thesis by Bush. Results indicate that the Z* test is more powerful than the competition at the available sample sizes of 5, 15 and 25 and alpha levels: 0.05 and 0.01. A relationship between the critical value and the sample size is investigated to allow for greater usage of the test statistic. Satisfactory values of fit are attained with a simple log-linear relationship ... Goodness-of-Fit Test, Weibull Distribution, Spacings.
A New Goodness Of Fit Test For The Weibull Distribution Based On Spacings
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Author : Mark C. Coppa
language : en
Publisher:
Release Date : 1993
A New Goodness Of Fit Test For The Weibull Distribution Based On Spacings written by Mark C. Coppa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
The critical values for a new goodness-of-fit test based on spacings are generated for the Weibull distribution when the shape parameter is known. The critical values are used for testing whether a set of observations follow a Weibull distribution when the scale and location parameters are unknown. A Monte Carlo simulation with 10,000 iterations is used to generate the critical values for sample sizes 5(5)35 at shape parameters k equal to 0.5(0.5)1.5 and for sample sizes 5(5)20 at shape parameters k = 2.0(1.0)4.0. A Monte Carlo power study of the Z* test statistic using 5000 iterations is accomplished using nine alternate distributions H sub A. The power is good to excellent when the null hypothesis Ho is from a skewed distribution(k 2.0). Power results at shape parameters k 2.0 are poor for all sample sizes considered. A comparison is made, at shape parameter 1.0, against the prominent competing goodness-of-fit test statistics. Data is obtained from a prior AFIT thesis by Bush. Results indicate that the Z* test is more powerful than the competition at the available sample sizes of 5, 15 and 25 and alpha levels: 0.05 and 0.01. A relationship between the critical value and the sample size is investigated to allow for greater usage of the test statistic. Satisfactory values of fit are attained with a simple log-linear relationship ... Goodness-of-Fit Test, Weibull Distribution, Spacings.
A New Sequential Goodness Of Fit Test For The Three Parameter Weibull Distribution With Known Shape Based On Skewness And Kurtosis
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Author : Jonathan C. Clough
language : en
Publisher:
Release Date : 1998-03-01
A New Sequential Goodness Of Fit Test For The Three Parameter Weibull Distribution With Known Shape Based On Skewness And Kurtosis written by Jonathan C. Clough and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-03-01 with Goodness-of-fit tests categories.
The Weibull distribution finds wide applicability across a broad spectrum of disciplines and is very prevalent in reliability theory. Consequently, numerous statistical tests have been developed to determine whether sample data can be adequately modeled with this distribution. Unfortunately, the majority of these goodness-of-fit tests involve a substantial degree of computational complexity. The study presented here develops and evaluates a new sequential goodness-of-fit test for the three-parameter Weibull distribution with a known shape that delivers power comparable to popular procedures while dramatically reducing computational requirements. The new procedure consists of two distinct tests, using only the sample skewness and sample kurtosis as test statistics. Critical values are derived using large Monte Carlo simulations for known shapes k=0.5(0.5)4 and sample sizes n=5(5)50. Attained significance levels for all combinations of the two tests between alpha=0.01(0.01)0.20 are also are approximated with Monte Carlo simulations and presented in a useful contour plot format. Extensive power studies against numerous alternate distributions demonstrate the test's excellent performance compared to popular EDF test statistics such as the Anderson-Darling and Cramer- von Mises tests. Recommendations are included on techniques to chose significance levels of the two component tests in a manner that should optimize power while maintaining the overall significance level.