Topp-Leone Nadarajah Haghighi dağılımı

In this paper, a three parameter model which can be used in modeling survival data, reliability problems and fatigue life studies has been studied. We derived explicit expressions for some of its statistical and mathematical identifying properties such as ordinary moments, generating function, incomplete moments and order statistics. The maximum likelihood estimations of model parameters were also obtained -being based on complete sample. We assessed the performance of the maximum likelihood estimators in terms of standard deviations, bias and mean squared errors by means of a simulation study. The usefulness of the model was illustrated by using a real data set. The proposed distribution provides better fits than some wellknown generalized distributions under the same criteria of comparison.Bu çalışmada yaşam verileri, güvenirlik problemleri ve yorulma ömrü çalışmalarında kullanılabilecek üç parametreli bir model üzerinde çalışılmıştır. Bu modele ait momentler, üreten fonksiyonlar, tamamlanmamış momentler ve sıra istatistikleri gibi istatistiksel ve matematiksel özellikler türetilmiştir. Tam örneklem durumuna dayalı olarak, model parametrelerinin sıradan en çok olabilirlik tahminleri elde edilmiştir. Bir simülasyon çalışması ile model parametrelerinin en çok olabilirlik tahmin edicilerinin performansları, standart sapma, yan ve hata kareler ortalamaları ile değerlendirilmiştir. Modelin kullanışlılığı, bir gerçek veri setine dayalı olarak gösterilmiştir. Önerilen dağılım bazı karşılaştırma kriterleri altında, literatürde iyi iyi bilinen birtakım dağılımlardan daha iyi uyum sağlamıştır

The Burr XII-Burr XII Distribution: Mathematical Properties and Characterizations

We introduce a new continuous distribution called the Burr XII-Burr XII distribution. Some of its properties are derived. The method of maximum likelihood is used to estimate the unknown parameters. An application is provided with details to illustrate the importance of the new. The new model provides adequate fits as compared to other related models with smallest values for A-IC, B-IC, CA-IC and HQ-IC. Characterization results are presented based on two truncated moments, hazard function as well as based on the conditional expectation

The Transmuted Weibull-Pareto Distribution

A new generalization of the Weibull-Pareto distribution called the transmuted Weibull-Pareto distribution is proposed and studied. Various mathematical properties of this distribution including ordinary and incomplete moments, quantile and generating functions, Bonferroni and Lorenz curves and order statistics are derived. The method of maximum likelihood is used for estimating the model parameters. The flexibility of the new lifetime model is illustrated by means of an application to a real data set

Oransal lindley fréchet dağılımının bazı teorik ve hesaplamalı yönleri

In this article, we study an extension of the Fréchet model by using the the odd Lindley-G family of distributions, which was introduced by [17]. Its some statistical properties such as quantile function, density shapes, moments, generating functions and order statistics are obtained. We estimate its parameters by maximum likelihood method. The Monte Carlo simulation is used for assessing the performance of the maximum likelihood method. The usefulness of the odd Lindley Fréchet model is illustrated by means of three real data sets.Bu çalışmada, Fréchet modelinin genişletilmiş bir versiyonu [17] tarafından önerilen oransal Lindley dağılım ailesi kullanılarak çalışılmıştır. Bu modele ait kuantil fonksiyonu, yoğunluk biçimi, momentler, üreten fonksiyon ve sıra istatistikleri gibi istatistiksel özellikleri elde edilmiştir. Model parametrelerinin en çok olabilirlik tahminleri elde edildi. En çok olabilirlik parametre tahminleri için bir simülasyon çalışılması verilmiştir. Önerilen modelin gerçek veri seti üzerindeki uygunluğu için üç veri analizi yapılmıştır

A New Discrete Distribution: Properties, Characterizations, Modeling Real Count Data, Bayesian and Non-Bayesian Estimations

In this work, a new discrete distribution which includes the discrete Burr-Hatke distribution is defined and studied. Relevant statistical properties are derived. The probability mass function of the new distribution can be right skewed with different shapes, bimodal and uniformed . Also, the corresponding hazard rate function can be monotonically decreasing , upside down , monotonically increasing , upside down increasing , and upside down-constant-increasing . A numerical analysis for the mean, variance, skewness, kurtosis and the index of dispersion is presented. The new distribution could be useful in the modeling of under-dispersed or overdispersed count data. Certain characterizations of the new distribution are presented. These characterizations are based on the conditional expectation of a certain function of the random variable and in terms of the hazard rate function. Bayesian and non-Bayesian estimation methods are considered. Numerical simulations for comparing Bayesian and non-Bayesian estimation methods are performed. The new model is applied for modeling carious teeth data and counts of cysts of kidneys data

A New Parametric Lifetime Distribution with Modified Chi-square Type Test for Right Censored Validation, Characterizations and Different Estimation Methods

A new three-parameter extension of the generalized Nadarajah-Haghighi model is introduced and studied. Some of its statistical properties are derived. Characterization results are presented. The failure rate can be increasing , decreasing , bathtub , upside-down , upside-down-constant , increasing-constant or constant . Different non-Bayesian estimation methods under uncensored scheme are considered. Numerical simulations are performed for comparing the estimation methods using different sample sizes. The censored Barzilai-Borwein algorithm is employed via a simulation study. Using the approach of the Bagdonavicius-Nikulin chi-square goodness-of-fit test for validation under the right censored data, we propose a modified chi-square goodness-of-fit test for the new model. Based on the maximum likelihood estimators on initial data, the modified Bagdonavicius-Nikulin chi-square goodness-of-fit test recovers the loss in information. The modified Bagdonavicius-Nikulin test for validation under the right censored data is applied to four real and right censored data sets. The new model is compared with many other competitive models by means of a real data set

The Burr X Exponentiated Weibull Model: Characterizations, Mathematical Properties and Applications to Failure and Survival Times Data

In this article, we introduce a new three-parameter lifetime model called the Burr X exponentiated Weibull model. The major justification for the practicality of the new lifetime model is based on the wider use of the exponentiated Weibull and Weibull models. We are motivated to propose this new lifetime model because it exhibits increasing, decreasing, bathtub, J shaped and constant hazard rates. The new lifetime model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be viewed as a suitable model for fitting the right skewed, symmetric, left skewed and unimodal data. We provide a comprehensive account of some of its statistical properties. Some useful characterization results are presented. The maximum likelihood method is used to estimate the model parameters. We prove empirically the importance and flexibility of the new model in modeling two types of lifetime data. The proposed model is a better fit than the Poisson Topp Leone-Weibull, the Marshall Olkin extended-Weibull, gamma-Weibull , Kumaraswamy-Weibull , Weibull-Fréchet, beta-Weibull, transmuted modified-Weibull, Kumaraswamy transmuted- Weibull, modified beta-Weibull, Mcdonald-Weibull and transmuted exponentiated generalized-Weibull models so it is a good alternative to these models in modeling aircraft windshield data as well as the new lifetime model is much better than the Weibull-Weibull, odd Weibull- Weibull, Weibull Log-Weibull, the gamma exponentiated-exponential and exponential exponential-geometric models so it is a good alternative to these models in modeling the survival times of Guinea pigs. We hope that the new distribution will attract wider applications in reliability, engineering and other areas of research

The Odd Power Lindley Generator of Probability Distributions: Properties, Characterizations and Regression Modeling

In this study, a new flexible family of distributions is proposed with its statistical properties as well as some useful characterizations. The maximum likelihood method is used to estimate the unknown model parameters by means of two simulation studies. A new regression model is proposed based on a special member of the proposed family called, the log odd power Lindley Weibull distribution. Residual analysis is conducted to evaluate the model assumptions. Four applications to real data sets are given to demonstrate the usefulness of the proposed model

The hjorth's IDB generator of distributions: properties, characterizations, regression modeling and applications

We introduce a new flexible class of continuous distributions via the Hjorth’s IDB model. We provide some mathematical prop-erties of the new family. Characterizations based on two truncated moments, conditional expectation as well as in terms of thehazard function are presented. The maximum likelihood method is used for estimating the model parameters. We assess the per-formance of the maximum likelihood estimators in terms of biases and mean squared errors by means of the simulation study.A new regression model as well as residual analysis are presented. Finally, the usefulness of the family is illustrated by means offour real data sets. The new model provides consistently better fits than other competitive models for these data sets