Objective Priors for Estimation of Extended Exponential Geometric Distribution

Ramos, Pedro Luiz; Moala, Fernando Antônio; Achcar, Jorge Alberto

doi:10.22237/jmasm/1414815060

Cited by 4 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shannon's Entropy from EEG distribution [ 9 ], which played a central role as a measure of the uncertainty associated with a random variable, is given by

…”

Section: Extended Exponential Geometric Distributionmentioning

confidence: 99%

See 1 more Smart Citation

Different Estimation Procedures for the Parameters of the Extended Exponential Geometric Distribution for Medical Data

Louzada

Ramos

Perdoná³

2016

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

We have considered different estimation procedures for the unknown parameters of the extended exponential geometric distribution. We introduce different types of estimators such as the maximum likelihood, method of moments, modified moments, L-moments, ordinary and weighted least squares, percentile, maximum product of spacings, and minimum distance estimators. The different estimators are compared by using extensive numerical simulations. We discovered that the maximum product of spacings estimator has the smallest mean square errors and mean relative estimates, nearest to one, for both parameters, proving to be the most efficient method compared to other methods. Combining these results with the good properties of the method such as consistency, asymptotic efficiency, normality, and invariance we conclude that the maximum product of spacings estimator is the best one for estimating the parameters of the extended exponential geometric distribution in comparison with its competitors. For the sake of illustration, we apply our proposed methodology in two important data sets, demonstrating that the EEG distribution is a simple alternative to be used for lifetime data.

show abstract

“…Shannon's Entropy from EEG distribution [ 9 ], which played a central role as a measure of the uncertainty associated with a random variable, is given by

…”

Section: Extended Exponential Geometric Distributionmentioning

confidence: 99%

“…Adamidis et al [ 3 ] derived the maximum likelihood estimators (MLE) for the unknown parameters of the EEG distribution. Ramos et al [ 9 ] developed a Bayesian analysis under noninformative priors. However, considering the frequentist approach, it is well known that, usually, for small samples, the MLE does not perform well.…”

Section: Introductionmentioning

confidence: 99%

Different Estimation Procedures for the Parameters of the Extended Exponential Geometric Distribution for Medical Data

Louzada

Ramos

Perdoná³

2016

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

show abstract

“…As such of the real dataset problem, related to the leukemia, free-survival times (in months) for the 50 autologous transplant patients. Many extensions from this present work can be considered, for instance, the parameters estimation may also be studied under an objective Bayesian analysis (Ramos et al, 2014 or using different classical methods (Louzada et al, 2016;Bakouch et al 2017). Other approach should be to include covariates under the assumption of Cox model, i.e., proportional hazards.…”

Section: Discussionmentioning

confidence: 99%

The Long Term Fréchet Distribution: Estimation, Properties and Its Application

Ramos¹

2017

BBIJ

View full text Add to dashboard Cite

In this paper a new long-term survival distribution is proposed. The so called long term Fréchet distribution allows us to fit data where a part of the population is not susceptible to the event of interest. This model may be used, for example, in clinical studies where a portion of the population can be cured during a treatment. It is shown an account of mathematical properties of the new distribution such as its moments and survival properties. As well is presented the maximum likelihood estimators (MLEs) for the parameters. A numerical simulation is carried out in order to verify the performance of the MLEs. Finally, an important application related to the leukemia free-survival times for transplant patients are discussed to illustrates our proposed distribution

show abstract

“…The posterior distribution obtained using this prior has interesting properties, such as invariance and consistency in marginalization and sample properties [ 18 ]. Some recent reference priors were obtained for the Pareto [ 19 ], Poisson-exponential [ 20 ], extended exponential-geometric [ 21 ], inverse Weibull [ 22 ], generalized half-normal [ 23 ] and Lomax [ 24 ] distributions.…”

Section: Background and Literaturementioning

confidence: 99%

Improved objective Bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime

et al. 2021

View full text Add to dashboard Cite

In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.

show abstract

Objective Priors for Estimation of Extended Exponential Geometric Distribution

Cited by 4 publications

References 26 publications

Different Estimation Procedures for the Parameters of the Extended Exponential Geometric Distribution for Medical Data

Different Estimation Procedures for the Parameters of the Extended Exponential Geometric Distribution for Medical Data

The Long Term Fréchet Distribution: Estimation, Properties and Its Application

Improved objective Bayesian estimator for a PLP model hierarchically represented subject to competing risks under minimal repair regime

Contact Info

Product

Resources

About