The beta generalized gamma distribution

Cordeiro, Gauss M.; Castellares, Fredy; Montenegro, Lourdes C.; Castro, Mário de

doi:10.1080/02331888.2012.658397

Cited by 36 publications

(30 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…() appears to contradict with the results given in Section 4 of Cordeiro et al. (), the former says that the moment generating function of the LPN distribution does not exist, whereas the latter gives explicit expressions for the moment generating function of a generalization of the LPN distribution. In addition, the first statement of the proof of Result 4 in Martínez‐Flórez et al.…”

Section: Commentsmentioning

confidence: 74%

See 1 more Smart Citation

The log‐power‐normal distribution is the exponentiated lognormal distribution

2014

View full text Add to dashboard Cite

show abstract

Section: Commentsmentioning

confidence: 74%

“…We mention Dey and Maiti (), Raja and Mir (), Castellares et al. (), Cordeiro et al (, , ), da Silva et al. (), and Nadarajah et al.…”

Section: Commentsmentioning

confidence: 96%

The log‐power‐normal distribution is the exponentiated lognormal distribution

2014

View full text Add to dashboard Cite

show abstract

“…Alternatively, other extensions of the GG distribution were developed for modeling lifetime data. For example, Cordeiro et al, 4 defined the exponentiated generalized gamma with applications, Pascoa et al, 5 introduced the Kumaraswamy generalized gamma distri bution, Ortega et al, 6 proposed the generalized gamma geometric distribution, Cordeiro et al, 7 studied the beta generalized gamma distribution and, more recently, Lucena et al, 8 defines the transmuted generalized gamma distribution and Silva et al, 9 proposed the generalized gamma power series class.…”

Section: Introductionmentioning

confidence: 99%

The Odd Log-Logistic Generalized Gamma Model: Properties, Applications, Classical And Bayesian Approach

Ortega¹

2017

BBIJ

View full text Add to dashboard Cite

We propose a new lifetime model called the odd log-logistic generalized gamma distri¬bution that can be easily interpreted. Some of its special models are discussed. We obtain general mathematical properties of this distribution including the ordinary moments, and quantile functions. We discuss parameter estimation by the maximum likelihood method and a Bayesian approach, where Gibbs algorithms along with metropolis steps are used to obtain the posterior summaries of interest for survival data with right censoring. Further, for different parameter settings, sample sizes and censoring percentages, we perform various simulations and evaluate the behavior of the estimators. The potentiality of the new distri¬bution is proved by means of two real data sets. In fact, the new distribution can produce better fits than some wellknown distributions

show abstract

“…Based on the betagenerated family and its variants, more generalized gamma distributions have been defined and studied. Some examples are the beta-gamma distribution by Kong et al (2007), the Kumaraswamy-gamma distribution by Cordeiro and de Castro (2011), the Kumaraswamy-generalized gamma distribution by de Pascoa et al (2011), and the beta generalized gamma distribution by Cordeiro et al (2013).…”

Section: Introductionmentioning

confidence: 99%

Family of generalized gamma distributions: Properties and applications

Alzaatreh¹,

Lee

Famoye

2015

HJMS

View full text Add to dashboard Cite

In this paper, a family of generalized gamma distributions, T -gamma family, has been proposed using the T -R{Y } framework. The family of distributions is generated using the quantile functions of uniform, exponential, log logistic, logistic and extreme value distributions. Several general properties of the T -gamma family are studied in details including moments, mean deviations, mode and Shannon's entropy. Three new generalizations of the gamma distribution which are members of the T -gamma family are developed and studied. The distributions in the T -gamma family are very flexible due to their various shapes. The distributions can be symmetric, skewed to the right, skewed to the left, or bimodal. Four data sets with various shapes are fitted by using members of the T -gamma family of distributions.

show abstract

The beta generalized gamma distribution

Cited by 36 publications

References 30 publications

The log‐power‐normal distribution is the exponentiated lognormal distribution

The log‐power‐normal distribution is the exponentiated lognormal distribution

The Odd Log-Logistic Generalized Gamma Model: Properties, Applications, Classical And Bayesian Approach

Family of generalized gamma distributions: Properties and applications

Contact Info

Product

Resources

About