Relevant bibliographies by topics / Generalized modified Weibull distribution

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Academic literature on the topic 'Generalized modified Weibull distribution'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Generalized modified Weibull distribution"

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Alizadeh, Morad, Muhammad Nauman Khan, Mahdi Rasekhi, and G.G Hamedani. "A New Generalized Modified Weibull Distribution." Statistics, Optimization & Information Computing 9, no. 1 (January 22, 2021): 17–34. http://dx.doi.org/10.19139/soic-2310-5070-1014.

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We introduce a new distribution, so called A new generalized modified Weibull (NGMW) distribution. Various structural properties of the distribution are obtained in terms of Meijer's $G$--function, such as moments, moment generating function, conditional moments, mean deviations, order statistics and maximum likelihood estimators. The distribution exhibits a wide range of shapes with varying skewness and assumes all possible forms of hazard rate function. The NGMW distribution along with other distributions are fitted to two sets of data, arising in hydrology and in reliability. It is shown that the proposed distribution has a superior performance among the compared distributions as evidenced via goodness--of--fit tests
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Cordeiro, Gaussm, Abdus Saboor, Muhammad Khan, and Serge Provost. "The transmuted generalized modified Weibull distribution." Filomat 31, no. 5 (2017): 1395–412. http://dx.doi.org/10.2298/fil1705395c.

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Canada EM provost@stats.uwo.ca AU Ortega Edwinm M. AF Universidade de S?o Paulo, Departamento de Ci?ncias Exatas, Piracicaba, Brazil EM edwin@usp.br KW Generalized modifiedWeibull distribution % Goodness-of-fit statistic % Lifetime data % Transmuted family % Weibull distribution KR nema A profusion of new classes of distributions has recently proven useful to applied statisticians working in various areas of scientific investigation. Generalizing existing distributions by adding shape parameters leads to more flexible models. We define a new lifetime model called the transmuted generalized modified Weibull distribution from the family proposed by Aryal and Tsokos [1], which has a bathtub shaped hazard rate function. Some structural properties of the new model are investigated. The parameters of this distribution are estimated using the maximum likelihood approach. The proposed model turns out to be quite flexible for analyzing positive data. In fact, it can provide better fits than related distributions as measured by the Anderson-Darling (A*) and Cram?r-von Mises (W*) statistics, which is illustrated by applying it to two real data sets. It may serve as a viable alternative to other distributions for modeling positive data arising in several fields of science such as hydrology, biostatistics, meteorology and engineering.
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Oluyede, Broderick, Shujiao Huang, and Tiantian Yang. "A New Class of Generalized Modified Weibull Distribution with Applications." Austrian Journal of Statistics 44, no. 3 (October 14, 2015): 45–68. http://dx.doi.org/10.17713/ajs.v44i3.36.

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A new five parameter gamma-generalized modified Weibull (GGMW) distribution which includes exponential, Rayleigh, modified Weibull, Weibull, gamma-modified Weibull, gamma-modified Rayleigh, gamma-modified exponential, gamma-Weibull, gamma-Rayleigh, and gamma-exponential distributions as special cases is proposed and studied. Some mathematical properties of the new class of distributions including moments, distribution of the order statistics, and Renyi entropy are presented. Maximum likelihood estimation technique is used to estimate the model parameters and applications to a real datasets to illustrates the usefulness of the proposed class of models are presented.
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Ahmad, Zubair, and Brikhna Iqbal. "Generalized Flexible Weibull Extension Distribution." Circulation in Computer Science 2, no. 4 (May 20, 2017): 68–75. http://dx.doi.org/10.22632/ccs-2017-252-11.

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In this article, a four parameter generalization of the flexible Weibull extension distribution so-called generalized flexible Weibull extension distribution is studied. The proposed model belongs to T-X family of distributions proposed by Alzaatreh et al. [5]. The suggested model is much flexible and accommodates increasing, unimodal and modified unimodal failure rates. A comprehensive expression of the numerical properties and the estimates of the model parameters are obtained using maximum likelihood method. By appropriate choice of parameter values the new model reduces to four sub models. The proposed model is illustrated by means of three real data sets.
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Aryal, Gokarna, and Ibrahim Elbatal. "On the Exponentiated Generalized Modified Weibull Distribution." Communications for Statistical Applications and Methods 22, no. 4 (July 31, 2015): 333–48. http://dx.doi.org/10.5351/csam.2015.22.4.333.

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Abdelall, Yassmen Y. "The odd generalized exponential modified Weibull distribution." International Mathematical Forum 11 (2016): 943–59. http://dx.doi.org/10.12988/imf.2016.6793.

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O. Oluyede, Broderick, Huybrechts F. Bindele, Boikanyo Makubate, and Shujiao Huang. "A New Generalized Log-logistic and Modified Weibull Distribution with Applications." International Journal of Statistics and Probability 7, no. 3 (April 17, 2018): 72. http://dx.doi.org/10.5539/ijsp.v7n3p72.

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A new generalized distribution called the {\em log-logistic modified Weibull} (LLoGMW) distribution is presented. This distribution includes many submodels such as the log-logistic modified Rayleigh, log-logistic modified exponential, log-logistic Weibull, log-logistic Rayleigh, log-logistic exponential, log-logistic, Weibull, Rayleigh and exponential distributions as special cases. Structural properties of the distribution including the hazard function, reverse hazard function, quantile function, probability weighted moments, moments, conditional moments, mean deviations, Bonferroni and Lorenz curves, distribution of order statistics, L-moments and R\'enyi entropy are derived. Model parameters are estimated based on the method of maximum likelihood. Finally, real data examples are presented to illustrate the usefulness and applicability of the model.
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Carrasco, Jalmar M. F., Edwin M. M. Ortega, and Gauss M. Cordeiro. "A generalized modified Weibull distribution for lifetime modeling." Computational Statistics & Data Analysis 53, no. 2 (December 2008): 450–62. http://dx.doi.org/10.1016/j.csda.2008.08.023.

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Merovci, Faton, and Ibrahim Elbatal. "A New Generalized of Exponentiated Modified Weibull Distribution." Journal of Data Science 13, no. 2 (April 8, 2021): 213–40. http://dx.doi.org/10.6339/jds.201504_13(2).0001.

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Shahzad, Mirza Naveed, Ehsan Ullah, and Abid Hussanan. "Beta Exponentiated Modified Weibull Distribution: Properties and Application." Symmetry 11, no. 6 (June 12, 2019): 781. http://dx.doi.org/10.3390/sym11060781.

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One of the most prominent statistical distributions is the Weibull distribution. The recent modifications in this distribution have enhanced its application but only in specific fields. To introduce a more generalized Weibull distribution, in this work beta exponentiated modified Weibull distribution is established. This distribution consolidate the exponential, skewed and symmetric shapes into one density. The proposed distribution also contains nineteen lifetime distributions as a special case, which shows the flexibility of the distribution. The statistical properties of the proposed model are derived and discussed, including reliability analysis and order statistics. The hazard function of the proposed distribution can have a unimodal, decreasing, bathtub, upside-down bathtub, and increasing shape that make it effective in reliability analysis. The parameters of the proposed model are evaluated by maximum likelihood and least squares estimation methods. The significance of the beta exponentiated modified Weibull distribution for modeling is illustrated by the study of real data. The numerical study indicates that the new proposed distribution gives better results than other comparable distributions.
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Dissertations / Theses on the topic "Generalized modified Weibull distribution"

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Carrasco, Jalmar Manuel Farfán. "Modelo de regressão log-Weibull modificado e a nova distribuição Weibull modificada generalizada." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-29022008-151018/.

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Neste trabalho propomos um modelo de regress~ao utilizando a distribuição Weibull modificado, esta distribuição pode ser usada para modelar dados de sobrevivência quando a de função de risco tem forma de U ou banheira. Assumindo dados censurados, é considerado os estimadores de máxima verossimilhança e Jackknife para os parâmetros do modelo proposto. Foram derivadas as matrizes apropriadas para avaliar influiência local sobre os parâmetros estimados considerando diferentes peturbações e também é apresen- tada alguma medidas de influência global. Para diferentes parâmetros fixados, tamanhos de amostra e porcentagem de censuras, varia simulações foram feitas para avaliar a distribuição empírica do resíduo deviance modificado e comparado coma distribuição normal padrão. Esses estudos sugerem que a distribuição empírica do resíduo devianve modificado para o modelo de regressão log-Weibull modificado com dados censurados aproxima-se de uma dis- tribuição normal padrão. Finalmente analisamos um conjunto de dados utilizando o modelo de regressão log-Weibull modificado. Uma nova distribuição de quatro parâmetros é definida para modelar dados de tempo de vida. Algumas propriedades da distribuição é discutida, assim como ilustramos com exemplos a aplicação dessa nova distribuição. Palavras-chaves: Modelo de regressão; Distribuição Weibull modificada; Distribuição weibull modificada generalizada; Análise de sensibilidade; Dados censurados; Análise de resíduo
In this paperwork are proposed a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider a classic and Jackknife estimator for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under diferent perturbation schemes and we also present some ways to perform global influence. Besides, for diferent parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the deviance modified residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extend for a martingale-type residual in log-modifiedWeibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the deviance modified residual are performed to select an appropriate model. A new four-parameter distribution is introduced. Various properties the new distribution are discussed. Illustrative examples based on real data are also given.
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Calsavara, Vinicius Fernando. "Modelos de sobrevivência com fração de cura usando um termo de fragilidade e tempo de vida Weibull modificada generalizada." Universidade Federal de São Carlos, 2011. https://repositorio.ufscar.br/handle/ufscar/4546.

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In survival analysis, some studies are characterized by having a significant fraction of units that will never suffer the event of interest, even if accompanied by a long period of time. For the analysis of long-term data, we approach the standard mixture model by Berkson & Gage, where we assume the generalized modified Weibull distribution for the lifetime of individuals at risk. This model includes several classes of models as special cases, allowing its use to discriminate models. The standard mixture model implicitly assume that those individuals experiencing the event of interest possess homogeneous risk. Alternatively, we consider the standard mixture model with a frailty term in order to quantify the unobservable heterogeneity among individuals. This model is characterized by the inclusion of a unobservable random variable, which represents information that can not or have not been observed. We assume multiplicative frailty with a gamma distribution. For the lifetime of individuals at risk, we assume the Weibull distribution, obtaining the frailty Weibull standard mixture model. For both models, we realized simulation studies with the purpose of analyzing the frequentists properties of estimation procedures. Applications to real data set showed the applicability of the proposed models in which parameter estimates were determined using the approaches of maximum likelihood and Bayesian.
Em análise de sobrevivência determinados estudos caracterizam-se por apresentar uma fração significativa de unidades que nunca apresentarão o evento de interesse, mesmo se acompanhados por um longo período de tempo. Para a análise de dados com longa duração, abordamos o modelo de mistura padrão de Berkson & Gage supondo que os tempos de vida dos indivíduos em risco seguem distribuição Weibull modificada generalizada. Este modelo engloba diversas classes de modelos como casos particulares, propiciando o uso deste para discriminar modelos. O modelo abordado assume implicitamente que todos os indivíduos que falharam possuem risco homogêneo. Alternativamente, consideramos o modelo de mistura padrão com um termo de fragilidade com o objetivo de quantificar a heterogeneidade não observável entre os indivíduos. Este modelo é caracterizado pela inclusão de uma variável aleatória não observável, que representa as informações que não podem ou que não foram observadas. Assumimos que a fragilidade atua de forma multiplicativa com distribuição gama. Para os tempos de vida dos indivíduos em risco consideramos a distribuição Weibull, obtendo o modelo de mistura padrão Weibull com fragilidade. Para os dois modelos realizamos estudos de simulação com o objetivo de analisar as propriedades frequentistas dos processos de estimação. Aplicações a conjunto de dados reais mostraram a aplicabilidade dos modelos propostos, em que a estimação dos parâmetros foram determinadas através das abordagens de máxima verossimilhança e Bayesiana.
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Sazak, Hakan Savas. "Estimation And Hypothesis Testing In Stochastic Regression." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/3/724294/index.pdf.

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Regression analysis is very popular among researchers in various fields but almost all the researchers use the classical methods which assume that X is nonstochastic and the error is normally distributed. However, in real life problems, X is generally stochastic and error can be nonnormal. Maximum likelihood (ML) estimation technique which is known to have optimal features, is very problematic in situations when the distribution of X (marginal part) or error (conditional part) is nonnormal. Modified maximum likelihood (MML) technique which is asymptotically giving the estimators equivalent to the ML estimators, gives us the opportunity to conduct the estimation and the hypothesis testing procedures under nonnormal marginal and conditional distributions. In this study we show that MML estimators are highly efficient and robust. Moreover, the test statistics based on the MML estimators are much more powerful and robust compared to the test statistics based on least squares (LS) estimators which are mostly used in literature. Theoretically, MML estimators are asymptotically minimum variance bound (MVB) estimators but simulation results show that they are highly efficient even for small sample sizes. In this thesis, Weibull and Generalized Logistic distributions are used for illustration and the results given are based on these distributions. As a future study, MML technique can be utilized for other types of distributions and the procedures based on bivariate data can be extended to multivariate data.
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Saaidia, Noureddine. "Sur les familles des lois de fonction de hasard unimodale : applications en fiabilité et analyse de survie." Thesis, Bordeaux 1, 2013. http://www.theses.fr/2013BOR14794/document.

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En fiabilité et en analyse de survie, les distributions qui ont une fonction de hasard unimodale ne sont pas nombreuses, qu'on peut citer: Gaussienne inverse ,log-normale, log-logistique, de Birnbaum-Saunders, de Weibull exponentielle et de Weibullgénéralisée. Dans cette thèse, nous développons les tests modifiés du Chi-deux pour ces distributions tout en comparant la distribution Gaussienne inverse avec les autres. Ensuite nousconstruisons le modèle AFT basé sur la distribution Gaussienne inverse et les systèmes redondants basés sur les distributions de fonction de hasard unimodale
In reliability and survival analysis, distributions that have a unimodalor $\cap-$shape hazard rate function are not too many, they include: the inverse Gaussian,log-normal, log-logistic, Birnbaum-Saunders, exponential Weibull and power generalized Weibulldistributions. In this thesis, we develop the modified Chi-squared tests for these distributions,and we give a comparative study between the inverse Gaussian distribution and the otherdistributions, then we realize simulations. We also construct the AFT model based on the inverseGaussian distribution and redundant systems based on distributions having a unimodal hazard ratefunction
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Salem, J. A. "Generalized reliability methodology applied to brittle anisotropic single crystals /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/7049.

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FERREIRA, Ricardo José. "Development of a mixed model using generalized renewal processes and the weibull distribution." Universidade Federal Rural de Pernambuco, 2016. http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7248.

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In order to analyze interventions in repairable systems, the literature contains several methodologies aiming to model the behavior of times between interventions. Such interventions can be modeled by Point Stochastic Processes in order to analyze the probabilistic behavior of times between events. Specifically, the Generalized Renewal Processes allow the study of times between interventions by measuring the quality of each intervention and the response of the system to these interventions — this is done by using the concept of virtual age. In such concept it is possible to apply two kinds of Kijima models (Type I and II). Therefore, this work presents a model capable of study the quality of interventions using up of a mix between the two Kijima models where it is possible to capture the performance on each of these interventions proportionally. Specifically, a new approach to virtual age of Kijima models is presented as well as mathematical properties of the Generalized Renewal Process using the Weibull distribution probability. Finally, the applicability of the model is checked in real data from some problems found in the literature.
Para analisar intervenções em sistemas reparáveis, a literatura apresenta diversas metodologias visando modelar o comportamento de tempos entre intervenções. Tais intervenções podem ser modeladas por Processos Estocásticos Pontuais visando analisar o comportamento probabilístico dos tempos entre eventos. Especificamente, os Processos de Renovação Generalizados permitem o estudo de tempos entre intervenções medindo a qualidade de impacto de cada intervenção e a resposta do sistema a tais intervenções - isto é feito utilizando o conceito de idade virtual. Em tal conceito é possível se aplicar dois tipos de modelos Kijima (tipo I e II).Sendo assim, esse trabalho apresenta um modelo capaz de estudar a qualidade de intervenções utilizando-se de uma mistura entre os dois modelos Kijima onde é possível capturar a atuação de cada um desses sobre as intervenções proporcionalmente. Especificamente, uma nova abordagem sobre a idade virtual dos modelos Kijima é apresentada, bem como propriedades matemáticas dos Processos de Renovação Generalizados utilizando a distribuição de probabilidadeWeibull. Por fim, a aplicabilidade do modelo é verificada em dados reais de alguns problemas presentes na literatura.
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BARROS, Patrícia Silva Nascimento. "Classes de distribuições Weibull generalizada: teorias e aplicações." Universidade Federal Rural de Pernambuco, 2015. http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5240.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
The Weibull distribution is very popular to model survival data. Many modi cations of the Weibull distribution have been proposed in recent years. Inspired by the notion of generalized gamma-generated family of distribution of Zografos e Balakrishnan, the Generalized Weibull Distributions Class is proposed. A comprehensive treatment of the mathematical properties of some new distribution is provided, expressions giving for the distribution function, density function, hazard function, moment generating function, characteristic function, mean, variance, skewness and kurtosis. Real data sets were modeled showing best ts, according the chosen criteria, were obtained by the new models. Thus for the Generalized Weibull Distributions Class, in spite of having more parameters to be estimated, the algorithms were able to best adjust the survival analysis data.
A distribuição Weibull é muito popular para modelar dados de sobrevida. Muitas modificações da distribuição Weibull foram propostas nos últimos anos. Inspirado pela noção da família gama-generalizada de distribuições de Zografos e Balakrishnan, é proposta, a classe de distribuições Weibull generalizada. Um tratamento compreensivo das propriedades matem áticas de algumas novas distribuições é feita, sendo encontradas as expressões para a função de distribuição, função densidade, função de risco, função geradora de momentos, função característica, m édia, variância, assimetria e curtose. Ajustou-se os novos modelos para conjuntos de dados reais veri cando, pelos critérios de escolha, que os melhores ajustes foram obtidos pelos novos modelos. Dessa forma a classe de distribuições Weibull Generalizada mesmo tendo mais parâmetros a serem estimados, os algoritmos foram capazes de ajustar os dados de análise de sobrevivência.
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Güimil, Fernando. "Comparing the Maximum Likelihood Method and a Modified Moment Method to fit a Weibull distribution to aircraft engine failure time data." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA337364.

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Güimil, Fernando. "Comparing the Maximum Likelihood Method and a Modified Moment Method to fit a Weibull distribution to aircraft engine failure time data." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/8112.

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This thesis provides a comparison of the accuracies of two methods for fitting a Weibull distribution to a set of aircraft engines time between failure data. One method used is the Maximum Likelihood Method and assumes that these engine failure times are independent. The other method is a Modified Method of Moments procedure and uses the fact that if time to failure T has a Weibull distribution with scale parameter lambda and shape parameter beta, then T(beta) has an exponential distribution with scale parameter lambda(beta). The latter method makes no assumption about independent failure times. A comparison is made from times that are randomly generated with a program. The program generates times in a manner that resembles the way in which engine failures occur in the real world for an engine with three subsystems. These generated operating times between failures for the same engine are not statistically independent. This comparison was extended to real data. Although the two methods gave good fits, the Maximum Likelihood Method produced a better fit than the Modified Method of Moments. Explanations for this fact are analyzed and presented in the conclusions
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Hofmann, Glenn, Erhard Cramer, N. Balakrishnan, and Gerd Kunert. "An Asymptotic Approach to Progressive Censoring." Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200201539.

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Progressive Type-II censoring was introduced by Cohen (1963) and has since been the topic of much research. The question stands whether it is sensible to use this sampling plan by design, instead of regular Type-II right censoring. We introduce an asymptotic progressive censoring model, and find optimal censoring schemes for location-scale families. Our optimality criterion is the determinant of the 2x2 covariance matrix of the asymptotic best linear unbiased estimators. We present an explicit expression for this criterion, and conditions for its boundedness. By means of numerical optimization, we determine optimal censoring schemes for the extreme value, the Weibull and the normal distributions. In many situations, it is shown that these progressive schemes significantly improve upon regular Type-II right censoring.
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Books on the topic "Generalized modified Weibull distribution"

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Güimil, Fernando. Comparing the Maximum Likelihood Method and a Modified Moment Method to fit a Weibull distribution to aircraft engine failure time data. Monterey, Calif: Naval Postgraduate School, 1997.

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Generalized Weibull Distributions Springerbriefs in Statistics. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

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Comparing the Maximum Likelihood Method and a Modified Moment Method to Fit a Weibull Distribution to Aircraft Engine Failure Time Data. Storming Media, 1997.

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Cheng, Russell. Examples of Embedded Distributions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0006.

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This chapter gives examples of probability distributions that, in their conventional parametrization, contain embedded models. Embeddedness is not intrinsic but depends on the parametrization. The simplest way to reveal and remove embeddedness is to reparametrize and make the log-likelihood, L, expandable as a Maclaurin series of one parameter, α‎: L = L0 + L1α‎ + L2α‎2 + … with L0 the log-likelihood of the embedded model hidden in the original parametrization. The quantity L1, rescaled using the information matrix, is the score statistic which can be used for formally comparing the original and embedded model fits. Embeddedness occurs in many distributions if there is a shifted threshold parameter. Examples given in the chapter are the Burr XII, gamma, generalized extreme value, inverse Gaussian, inverted gamma, logistic, loglogistic, lognormal, loggamma, Pareto, and Weibull distributions. Another interesting example occurs in early parametrizations of the stable law distribution.
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Book chapters on the topic "Generalized modified Weibull distribution"

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Lai, Chin-Diew. "Weibull Distribution." In Generalized Weibull Distributions, 1–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39106-4_1.

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Corrêa, T., I. Lins, M. Moura, and E. López. "Generalized renewal process based on the q-Weibull distribution for reliability applications." In Risk, Reliability and Safety: Innovating Theory and Practice, 1087–93. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315374987-164.

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Yan, Wang, and Shi Yimin. "Statistical Inference of the Competing Risks Model with Modified Weibull Distribution Under Adaptive Type-II Progressive Hybrid Censoring." In Stochastic Models in Reliability, Network Security and System Safety, 295–312. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0864-6_15.

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Voinov, Vassilly, Roza Alloyarova, and Natalie Pya. "A Modified Chi-squared Goodness-of-fit Test for the Three-parameter Weibull Distribution and its Applications in Reliability." In Mathematical Methods in Survival Analysis, Reliability and Quality of Life, 189–202. London, UK: ISTE, 2010. http://dx.doi.org/10.1002/9780470610985.ch13.

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Chen, (Din) Ding-Geng, and Yuhlong Lio. "A Family of Generalized Rayleigh-Exponential-Weibull Distribution and Its Application to Modeling the Progressively Type-I Interval Censored Data." In Emerging Topics in Statistics and Biostatistics, 529–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42196-0_23.

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Krupiński, Robert. "Modified Moment Method Estimator for the Shape Parameter of Generalized Gaussian Distribution for a Small Sample Size." In Computer Information Systems and Industrial Management, 420–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40925-7_39.

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Mudasir, Sofi, and S. P. Ahmad. "Parameter Estimation of Weighted New Weibull Pareto Distribution." In Bayesian Analysis and Reliability Estimation of Generalized Probability Distributions, 13–29. AIJR Publisher, 2019. http://dx.doi.org/10.21467/books.44.2.

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Youssef, Bassant, Scott F. Midkiff, and Mohamed R. M. Rizk. "SNAM." In Advanced Methods for Complex Network Analysis, 215–36. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9964-9.ch009.

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Complex networks are characterized by having a scale-free power-law (PL) degree distribution, a small world phenomenon, a high average clustering coefficient, and the emergence of community structure. Most proposed models did not incorporate all of these statistical properties and neglected incorporating the heterogeneous nature of network nodes. Even proposed heterogeneous complex network models were not generalized for different complex networks. We define a novel aspect of node-heterogeneity which is the node connection standard heterogeneity. We introduce our novel model “settling node adaptive model” SNAM which reflects this new nodes' heterogeneous aspect. SNAM was successful in preserving PL degree distribution, small world phenomenon and high clustering coefficient of complex networks. A modified version of SNAM shows the emergence of community structure. We prove using mathematical analysis that networks generated using SNAM have a PL degree distribution.
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Kwitt, Roland, Peter Meerwald, and Andreas Uhl. "Blind Detection of Additive Spread-Spectrum Watermarking in the Dual-Tree Complex Wavelet Transform Domain." In Crime Prevention Technologies and Applications for Advancing Criminal Investigation, 53–65. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1758-2.ch005.

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In this paper, the authors adapt two blind detector structures for additive spread-spectrum image watermarking to the host signal characteristics of the Dual-Tree Complex Wavelet Transform (DT-CWT) domain coefficients. The research is motivated by the superior perceptual characteristics of the DT-CWT and its active use in watermarking. To improve the numerous existing watermarking schemes in which the host signal is modeled by a Gaussian distribution, the authors show that the Generalized Gaussian nature of Dual-Tree detail subband statistics can be exploited for better detector performance. This paper finds that the Rao detector is more practical than the likelihood-ratio test for their detection problem. The authors experimentally investigate the robustness of the proposed detectors under JPEG and JPEG2000 attacks and assess the perceptual quality of the watermarked images. The results demonstrate that their alterations allow significantly better blind watermark detection performance in the DT-CWT domain than the widely used linear-correlation detector. As only the detection side has to be modified, the proposed methods can be easily adopted in existing DT-CWT watermarking schemes.
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Conference papers on the topic "Generalized modified Weibull distribution"

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Abid, Salah Hamza, Nadia Hashim Al-Noor, and Mohammad Abd Alhussein Boshi. "On the generalized inverse Weibull distribution." In CURRENT TRENDS IN RENEWABLE AND ALTERNATE ENERGY. Author(s), 2019. http://dx.doi.org/10.1063/1.5095087.

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Peng, Weiwen, Hua Zhang, Hong-Zhong Huang, Zhean Gong, and Yu Liu. "Satellite reliability modeling with modified Weibull extension distribution." In 2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2012. http://dx.doi.org/10.1109/icqr2mse.2012.6246218.

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Yenilmez, Ismail, Yeliz Mert Kantar, Ibrahim Arik, and Ilhan Usta. "Analysis of the Modified Weibull Distribution for Estimation of Wind Speed Distribution." In the The International Conference. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2832987.2833059.

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Xiao, Han, Daquan Cai, and Wei Ou. "United Estimation of Weibull Distribution Parameters Based on Modified ABC." In 2016 Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC). IEEE, 2016. http://dx.doi.org/10.1109/imccc.2016.45.

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Renyan Jiang. "A modified MPS method for fitting the 3-parameter Weibull distribution." In 2013 International Conference on Quality, Reliability, Risk, Maintenance and Safety Engineering (QR2MSE). IEEE, 2013. http://dx.doi.org/10.1109/qr2mse.2013.6625731.

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Nan Zhang, Gang Cui, and Hong-wei Liu. "A finite queuing model with generalized modified Weibull testing effort for software reliability." In 2011 International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2011. http://dx.doi.org/10.1109/iccsnt.2011.6181985.

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Reddy, Galiveeti Hemakumar, Aditya N. Koundinya, More Raju, Sadhan Gope, and Chinmaya Behera. "Lifetime Estimation of Electrical Equipment in Distribution system using Modified 3-Parameter Weibull Distribution." In 2021 International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C). IEEE, 2021. http://dx.doi.org/10.1109/icdi3c53598.2021.00013.

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Li, Changhai, Yunlong Teng, Lulu An, and Qiuge Dan. "Imprecise reliability of lifetime data based on three-parameter generalized inverse Weibull distribution." In 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2019. http://dx.doi.org/10.1109/isgt-asia.2019.8881238.

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Salim, Omar M., Hassen Taher Dorrah, and Mahmoud Adel Hassan. "A Generalized Cascaded Approach to Estimate Missing Wind Data Using Multivariate Weibull Distribution Network." In 2020 12th International Conference on Electrical Engineering (ICEENG). IEEE, 2020. http://dx.doi.org/10.1109/iceeng45378.2020.9171741.

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Montes, Martin A., Anni K. Vuorenkoski, and Fraser R. Dalgleish. "An interpretation of underwater LiDAR waveforms based on a modified Weibull probability distribution function." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729978.

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