Inference for exponentiated general class of distributions based on record values

Statistical prediction is one of the most important problems in life testing; it has been applied in medicine, engineering, business and other areas as well. In this paper, the exponentiated generalized xgamma distribution is introduced as an application on the exponentiated generalized general class of distributions. Bayesian point and interval prediction of exponentiated generalized xgamma distribution based on dual generalized order statistics are considered. All results are specialized to lower records. The results are verified using simulation study as well as applications to real data sets to demonstrate the flexibility and potential applications of the distribution.

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“…, from EGGC distribution is obtained by substituting ( 14) in (13) . Then which can be rewritten as .…”

Section: Bayesian Prediction For Exponentiated Generalized General Class Of Distributionsmentioning

confidence: 99%

“…Many authors focused on the EG distributions and its applications; for example, Oguntunde et al [9], Yousof et al [10], De Andrade et al [11], Mustafa et al [12], Sindi et al [13]], Nasiru et al [14], Abbas et al [15] and Oluyede et al [16].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Prediction for Exponentiated Generalized Xgamma Distribution Based on Dual Generalized Order Statistics with Application to Poverty and COVID-19 Mortality Rates

El-Kader

AL-Fattah

AL-Dayian

et al. 2021

JAMCS

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“…Many authors studied record values and the associated statistics such as [1][2][3][4][5][6]. Furthermore, there are several studies which discussed some inferential methods based on record values for the Rayleigh [7,8], Weibull [9], inverse Weibull [10,11], exponentiated Family [12,13], Lomax [14,15], power Lindley model [16], exponentiated Weibull [17,18], and normal distribution [19].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Estimations under the Weighted LINEX Loss Function Based on Upper Record Values

Al-Duais

2021

Complexity

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The essential objective of this research is to develop a linear exponential (LINEX) loss function to estimate the parameters and reliability function of the Weibull distribution (WD) based on upper record values when both shape and scale parameters are unknown. We perform this by merging a weight into LINEX to produce a new loss function called the weighted linear exponential (WLINEX) loss function. Then, we utilized WLINEX to derive the parameters and reliability function of the WD. Next, we compared the performance of the proposed method (WLINEX) in this work with Bayesian estimation using the LINEX loss function, Bayesian estimation using the squared-error (SEL) loss function, and maximum likelihood estimation (MLE). The evaluation depended on the difference between the estimated parameters and the parameters of completed data. The results revealed that the proposed method is the best for estimating parameters and has good performance for estimating reliability.

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Inference for exponentiated general class of distributions based on record values

Cited by 2 publications

References 15 publications

Bayesian Prediction for Exponentiated Generalized Xgamma Distribution Based on Dual Generalized Order Statistics with Application to Poverty and COVID-19 Mortality Rates

Bayesian Prediction for Exponentiated Generalized Xgamma Distribution Based on Dual Generalized Order Statistics with Application to Poverty and COVID-19 Mortality Rates

Bayesian Estimations under the Weighted LINEX Loss Function Based on Upper Record Values

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