DSpace Arşivi :: by Yazar "Yousof, Haitham M." değerine göre listeleniyor

Yazar "Yousof, Haitham M." seçeneğine göre listele

Listeleniyor 1 - 20 / 21

A novel chen extension: Theory, characterizations and different estimation methods
(Ada Academica, 2022) Yousof, Haitham M.; Korkmaz, Mustafa Çağatay; Hamedani G.G.; Ibrahim, Mohamed
In this work, we derive a novel extension of Chen distribution. Some statistical properties of the new model are derived. Numerical analysis for mean, variance, skewness and kurtosis is presented. Some characterizations of the proposed distribution are presented. Different classical estimation methods under uncensored schemes such as the maximum likelihood, Anderson-Darling, weighted least squares and right-tail Anderson–Darling methods are considered. Simulation studies are performed in order to compare and assess the above-mentioned estimation methods. For comparing the applicability of the four classical methods, two application to real data set are analyzed.
The Burr X Pareto distribution: properties, applications and VaR estimation
(MDPI, 2018) Korkmaz, Mustafa Çağatay; Altun, Emrah; Yousof, Haitham M.; Afify, Ahmed Z.; Nadarajah, Saralees
In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate Value-at-Risk (VaR) by means of the proposed distribution. We compare the distribution with a few other models to show its versatility in modelling data with heavy tails. VaR estimation with the Burr X Pareto distribution is presented using time series data, and the new model could be considered as an alternative VaR model against the generalized Pareto model for financial institutions.
The exponential lindley odd log-logistic-g family: properties, characterizations and applications
(Atlantis Press, 2018) Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Hamedani, Gholamhossein G.
A new family of distributions called the exponential Lindley odd log-logistic G family is introduced and studied. The new generator generalizes three newly defined G families and also defines two new G families We provide some mathematical properties of the new family. Characterizations based on truncated moments as well as in terms of the hazard function are presented. The maximum likelihood is used for estimating the model parameters. We assess the performance of the maximum likelihood estimators in terms of biases and mean squared errors by means of a simulation study. Finally, the usefulness of the family is illustrated by means of three real data sets. The new model provides consistently better fits than other competitive models for these data sets.
The generalized odd weibull generated family of distributions: statistical properties and applications
(Univ Punjab, 2018) Korkmaz, Mustafa Çağatay; Alizadeh, Morad; Yousof, Haitham M.; Butt, Nadeem Shafique
In this work, we propose a new class of lifetime distributions calledthe generalized odd Weibull generatedfamily. It can provide better fits than some of the well known lifetime models and this fact represents a good characterization of this family. Some of its mathematical properties are derived. The maximum likelihood method is used for estimating the model parameters. We study the behaviour of the estimators by means of two Monte Carlo simulations. The importance of the family illustrated by means of two applications to real data sets.
The hjorth's IDB generator of distributions: properties, characterizations, regression modeling and applications
(Atlantis Press, 2020) Korkmaz, Mustafa Çağatay; Altun, Emrah; Yousof, Haitham M.; Hamedani, G. G.
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.
A new extended g family of continuous distributions with mathematical properties, characterizations and regression modeling
(Univ Punjab, 2018) Hamedani, G. G.; Altun, Emrah; Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Butt, Nadeem Shafique
We propose a new extended G family of distributions. Some of its structural properties are derived and some useful characterization results are presented. The maximum likelihood method is used to estimate the model parameters by means of graphical and numerical Monte Carlo simulation study. The flexibility of the new family illustrated by means of two real data sets. Moreover, we introduce a new log-location regression model based on the proposed family. The martingale and modified deviance residuals are defined to detect outliers and evaluate the model assumptions. The potentiality of the new regression model is illustrated by means of a real data set.
A new flexible lifetime model with log-location regression modeling, properties and applications
(Taru Publication, 2019) Korkmaz, Mustafa Çağatay; Altun, Emrah; Alizadeh, Morad; Yousof, Haitham M.
In this paper, we propose a new lifetime model for modeling fatigue lifetime data. Some of its statistical properties are obtained. The method of maximum likelihood is used to estimate the model parameters. Simulation study is given to demonstrate the maximum likelihood estimators of the parameters of proposed model. Moreover, a new log-location-scale regression model is introduced with its residuals analysis. Three applications to real data sets are given to prove the usefulness of proposed model in real data modeling.
A new two-parameter lifetime model
(Springer Science and Business Media Deutschland GmbH, 2021) Yousof, Haitham M.; Korkmaz, Mustafa Çağatay; Sen, Subhradev
A new two parameter life time model, which accommodates increasing, decreasing, bathtub, and a broad variety of monotone failure rates, has been introduced in this article. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, moment of residual and reversed residual lives have been derived. The maximum likelihood has been proposed for estimating the model parameters. The importance and flexibility of the new distribution has been illustrated by means of an applications to real data set supported by a Monte-Carlo simulation study.
Odd lindley-lomax model: Statistical properties and applications
(Univ Punjab, 2019) Ali, M. Masoom; Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Butt, Nadeem Shafique
In this work, we focus on some new theoretical and computational aspects of the Odd LindleyLomax model. The maximum likelihood estimation method is used to estimate the model parameters. We show empirically the importance and flexibility of the new model in modeling two types of aircraft windshield lifetime data. This model is much better than exponentiated Lomax, gamma Lomax, beta Lomax and other Lomax models so that the Odd Lindley-Lomax lifetime model is a good alternative to these models in modeling aircraft windshield data. A Monte Carlo simulation study is used to assess the performance of the maximum likelihood estimators.
On Burr III Marshal Olkin family: development, properties, characterizations and applications
(Springer, 2019) Bhatti, Fiaz Ahmad; Hamedani G.G.; Korkmaz, Mustafa Çağatay; Cordeiro, Gauss M.; Yousof, Haitham M.; Ahmad, Munir
In this paper, a flexible family of distributions with unimodel, bimodal, increasing, increasing and decreasing, inverted bathtub and modified bathtub hazard rate called Burr III-Marshal Olkin-G (BIIIMO-G) family is developed on the basis of the T-X family technique. The density function of the BIIIMO-G family is arc, exponential, left- skewed, right-skewed and symmetrical shaped. Descriptive measures such as quantiles, moments, incomplete moments, inequality measures and reliability measures are theoretically established. The BIIIMO-G family is characterized via different techniques. Parameters of the BIIIMO-G family are estimated using maximum likelihood method. A simulation study is performed to illustrate the performance of the maximum likelihood estimates (MLEs). The potentiality of BIIIMO-G family is demonstrated by its application to real data sets.
On the new modified burr XII distribution: Development, properties, characterizations and applications
(University of Punjab (new Campus), 2023) Bhatti, Fiaz Ahmad; Hamedani G.G.; Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Ahmad, Munir
A new distribution with flexible hazard rate function is introduced which is called new modified Burr XII (NMBXII) distribution. The proposed distribution is derived from the T-X family technique and compounding the generalized Nadarajah–Haghighi (GNH) and gamma distributions. We highlighted the shapes of NMBXII density and failure rate functions. The density function of NMBXII model can take shapes such as J, reverse J, positively skewed and symmetrical. The proposed model can produce almost all types of failure rates such as increasing, decreasing, increasing-decreasing, decreasing-increasing, bimodal, inverted bathtub and modified bathtub. To show the importance of the proposed distribution, we established various mathematical properties such as quantiles, moments, incomplete moments, inequality measures, residual life functions and reliability measures theoretically. We have characterized the NMBXII distribution via two techniques. We addressed the maximum likelihood estimation technique for model parameters. The precision of the MLEs is estimated via a simulation study. We have considered three real data sets for applications to demonstrate the potentiality and utility of the NMBXII model. Then, we have established empirically that the proposed model is suitable for tax revenue, time periods between successive earthquakes and flood discharges applications. Finally, various model selection criteria, the goodness of fit statistics and graphical tools were used to examine the adequacy of the NMBXII distribution.
On the Unit-Chen distribution with associated quantile regression and applications
(De Gruyter Open Ltd, 2022) Korkmaz, Mustafa Çağatay; Altun, Emrah; Chesneau, Christophe; Yousof, Haitham M.
In this paper, a new distribution defined on (0, 1) is introduced. It is obtained by the transformation of a positive random variable following the Chen distribution with respect to the inverted exponential function. Basic distributional properties of the newly defined distribution are studied. Then, as a statistical model, we examine different methods of estimation for related parameters. We assess the performance of the obtained estimators by a complete simulation study. Subsequently, the quantile regression model based on the proposed distribution is introduced. Applications of the proposed models to real data sets show that they have better modeling capabilities than fair competitors. © 2022 Mathematical Institute Slovak Academy of Sciences.
Some theoretical and computational aspects of the odd lindley fréchet distribution
(Aktüerya Derneği, 2017) Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Ali, M. Masoom
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.
The exponentiated burr XII power series distribution: Properties and applications
(Multidisciplinary Digital Publishing Institute (MDPI), 2019) Nasir, Arslan; Yousof, Haitham M.; Jamal, Farrukh; Korkmaz, Mustafa Çağatay
In this work, we introduce a new Burr XII power series class of distributions, which is obtained by compounding exponentiated Burr XII and power series distributions and has a strong physical motivation. The new distribution contains several important lifetime models. We derive explicit expressions for the ordinary and incomplete moments and generating functions. We discuss the maximum likelihood estimation of the model parameters. The maximum likelihood estimation procedure is presented. We assess the performance of the maximum likelihood estimators in terms of biases, standard deviations, and mean square of errors by means of two simulation studies. The usefulness of the new model is illustrated by means of three real data sets. The new proposed models provide consistently better fits than other competitive models for these data sets.
The marshall-olkin generalized G poisson family of distributions
(ISOSS PUBLICATIONS, 2018) Korkmaz, Mustafa Çağatay; Yousof, Haitham M.; Hamedani G.G.; Ali, M. Masoom
In this paper, we propose a new class of lifetime distributions called the Marshall-Olkin Generalized G Poisson family. The proposed family of distributions is constructed by compounding the Marshall-Olkin Generalized distribution with the truncated Poisson distribution. It can provide better fits than some of the known lifetime distributions and this fact represents a good characterization of this new family. Some useful characterizations for the new family are presented. The maximum likelihood method is used for estimating the model parameters. The importance and flexibility of the new family are illustrated by means of an application to a real data set.
The one-parameter Odd Lindley exponential model: Mathematical properties and applications
(Walter de Gruyter GmbH, 2017) Korkmaz, Mustafa Çağatay; Yousof, Haitham M.
In this article, an exponential model with only one shape parameter, which can be used in modeling survival data, reliability problems and fatigue life studies, is studied. We derive explicit expressions for some of its statistical and mathematical quantities including the ordinary moments, generating function, incomplete moments, order statistics, moment of residual life and reversed residual life. The model parameter is estimated by using the maximum likelihood method. A real data application is given to illustrate the flexibility of the model. We assess the performance of the maximum likelihood estimators in terms of biases and mean squared errors by means of a simulation study.
Topp-Leone Nadarajah-Haghighi distribution
(Aktüerya Derneği, 2017) Yousof, Haitham M.; Korkmaz, Mustafa Çağatay
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.
The type I quasi lambert family: properties, characterizations and different estimation methods
(Univ Punjab, 2021) Hamedani, Gholamhossein G.; Korkmaz, Mustafa Çağatay; Butt, Nadeem Shafique; Yousof, Haitham M.
A new G family of probability distributions called the type I quasi Lambert family is defined and applied for modeling real lifetime data. Some new bivariate type G families using "Farlie-Gumbel-Morgenstern copula", "modified Farlie-Gumbel-Morgenstern copula", "Clayton copula" and "Renyi's entropy copula" are derived. Three characterizations of the new family are presented. Some of its statistical properties are derived and studied. The maximum likelihood estimation, maximum product spacing estimation, least squares estimation, Anderson-Darling estimation and Cramer-von Mises estimation methods are used for estimating the unknown parameters. Graphical assessments under the five different estimation methods are introduced. Based on these assessments, all estimation methods perform well. Finally, an application to illustrate the importance and flexibility of the new family is proposed
The type II quasi lambert G family of probability distributions
(UNIV PUNJAB, 2022) Hamedani, G. G.; Korkmaz, Mustafa Çağatay; Butt, Nadeem Shafique; Yousof, Haitham M.
Probability distributions and their families play an effective role in statistical modeling and statistical analysis. Recently, researchers have been increasingly interested in generating new families with high flexibility and low number of milestones. We propose and study a new family of continuous distributions. Relevant properties are presented. Many bivariate versions of the new family are derived under the Farlie-Gumbel-Morgenstern copula, modified Farlie-Gumbel-Morgenstern copula, Clayton copula, entropy copula and Ali-Mikhail-Haq copula. We present two characterizations of the new family. Different estimation methods such as the maximum likelihood estimation, maximum product spacing estimation, least squares estimation, weighted least squares estimation, Anderson-Darling estimation and the Cramer-von Mises estimation methods are considered. Simulation studies for comparing estimation methods are performed based on the baseline Lindley model. Two real data sets are analyzed for comparing the competitive models.
The Weibull Marshall-Olkin family: Regression model and application to censored data
(Taylor & Francis Inc, 2019) Korkmaz, Mustafa Çağatay; Cordeiro, Gauss M.; Yousof, Haitham M.; Pescim, Rodrigo R.; Afify, Ahmed Z.; Nadarajah, Saralee
We introduce a new class of distributions called the Weibull Marshall-Olkin-G family. We obtain some of its mathematical properties. The special models of this family provide bathtub-shaped, decreasing-increasing, increasing-decreasing-increasing, decreasing-increasing-decreasing, monotone, unimodal and bimodal hazard functions. The maximum likelihood method is adopted for estimating the model parameters. We assess the performance of the maximum likelihood estimators by means of two simulation studies. We also propose a new family of linear regression models for censored and uncensored data. The flexibility and importance of the proposed models are illustrated by means of three real data sets.

Yazar "Yousof, Haitham M." seçeneğine göre listele

Sayfa Başına Sonuç

Sıralama seçenekleri