Yazar "Butt, Nadeem Shafique" seçeneğine göre listele

Listeleniyor 1 - 5 / 5
  • Küçük Resim
    Öğe
    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.
  • Küçük Resim
    Öğe
    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.
  • Küçük Resim
    Öğe
    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.
  • Küçük Resim
    Öğe
    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
  • Küçük Resim
    Öğe
    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.