A new generalized two-sided class of distributions with an emphasis on two-sided generalized normal distribution

Korkmaz, Mustafa Ç.; Genç, Alі İ.

doi:10.1080/03610918.2015.1005233

Cited by 35 publications

(17 citation statements)

References 31 publications

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“…Remark 3.1. If = 0, we have the pdf and cdf of the TSG-G family introduced by Korkmaz and Genç [1]. If = 1, = 1, and = 0, we have the pdf of the base distribution.…”

Section: Transmuted Two-sided Generalized-g Family Of the Distributionsmentioning

confidence: 99%

“…The Kullback Leibler divergence (or relative entropy) is an informational measure for comparing the similarity between two pdfs. The Kullback Leibler divergence between the proposed distribution TTSG − G and the TSG − G distribution, introduced by Korkmaz and Genç [1], is obtained as…”

Section: Kullback Leibler Divergencementioning

confidence: 99%

“…and Genç [11] considered the log transformation of the TSP distribution instead of uniform distribution and introduced a generalization of the exponential distribution. Korkmaz and Genç [1] extended the idea of two-sidedness to other ordinary distributions like normal and introduced the two-sided generalized normal distribution.…”

Section: Introductionmentioning

confidence: 99%

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A New Generalized Two-Sided Class of the Distributions Via New Transmuted Two-Sided Bounded Distribution

Kharazmi¹,

Zargar²

2019

JSTA

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In the present paper, we first consider a generalization of the standard two-sided power distribution so-called the transmuted two-sided distribution, and then extend proposed idea to generalized two-sided class of distributions, introduced by Korkmaz and Genç [1]. Some statistical and reliability properties including explicit expressions for quantiles, hazard rate function, order statistics, and maximum likelihood estimation are obtained in general setting. Generalized transmuted two-sided exponential distribution is considered as a especial case and denoted with the name TTSG − G. A simulation study is presented to investigate the bias and mean square error of the maximum likelihood estimators. We use a real data set and obtain the maximum likelihood and parametric bootstrap estimator of the parameters of TTSG − G distribution. Finally, the superiority of the new model to some common statistical distributions is shown through the different criteria of selection model including log-likelihood values, Akaike information criterion, and Kolmogorov Smirnov test statistic values.

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“…Remark 3.1. If = 0, we have the pdf and cdf of the TSG-G family introduced by Korkmaz and Genç [1]. If = 1, = 1, and = 0, we have the pdf of the base distribution.…”

Section: Transmuted Two-sided Generalized-g Family Of the Distributionsmentioning

confidence: 99%

Section: Kullback Leibler Divergencementioning

confidence: 99%

See 1 more Smart Citation

A New Generalized Two-Sided Class of the Distributions Via New Transmuted Two-Sided Bounded Distribution

Kharazmi¹,

Zargar²

2019

JSTA

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“…They were pioneered by Gupta et al (1998) who proposed the exponentiated-G (Exp-G) class, which consists of raising the cumulative distribution function (cdf) to a positive power parameter. Many other classes can be cited such as the T-X family by Alzaatreh et al (2013), the Lomax-G by Cordeiro et al (2014), Burr X generator by Yousof et al (2016), the generalized two-sided class of distributions by Korkmaz and Genç (2017), the Burr XII generator by Cordeiro et al (2018), among others.…”

Section: Introductionmentioning

confidence: 99%

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

Korkmaz¹,

Altun²,

Yousof³

et al. 2019

IJSP

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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.

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“…These generalized distributions give more flexibility by adding one or more parameters to the baseline model. Many classes can be cited such as the Marshall-Olkin-G family by Marshall and Olkin [25], transmuted exponentiated generalized-G family by Yousof et al [34], Burr X-G by Yousof et al [35], type I half-logistic family by Cordeiro et al [12], Zografos-Balakrishnan odd log-logistic family of distributions by Cordeiro et al [13], a new generalized two-sided family of distributions by Korkmaz and Genç [22], generalized odd log-logistic family by Cordeiro et al [10], odd-Burr generalized family by Alizadeh et al [4], beta Weibull G by Yousof et al [36], exponentiated generalized-G Poisson family by Aryal and Yousof [8], type I general exponential class by Hamedani et al [20] and beta transmuted-H by Afify et al [2] among others.…”

Section: Introductionmentioning

confidence: 99%

The Exponential Lindley Odd Log-Logistic-G Family: Properties, Characterizations and Applications

Korkmaz¹,

Yousof²,

Hamedani³

2018

JSTA

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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.

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A new generalized two-sided class of distributions with an emphasis on two-sided generalized normal distribution

Cited by 35 publications

References 31 publications

A New Generalized Two-Sided Class of the Distributions Via New Transmuted Two-Sided Bounded Distribution

A New Generalized Two-Sided Class of the Distributions Via New Transmuted Two-Sided Bounded Distribution

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

The Exponential Lindley Odd Log-Logistic-G Family: Properties, Characterizations and Applications

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