Estimation and Prediction in a Two-Parameter Exponential Distribution Based on k-Record Values under LINEX Loss Function

2005 ◽  
Vol 34 (4) ◽  
pp. 795-805 ◽  
Author(s):  
J. AHMADI ◽  
M. DOOSTPARAST ◽  
A. PARSIAN
Keyword(s):  
Exponential Distribution ◽  
Loss Function ◽  
Record Values ◽  
Linex Loss Function ◽  
Estimation And Prediction ◽  
Linex Loss ◽  
Two Parameter

scholarly journals Bayesian Estimates Based On Record Values Under Weighted LINEX Loss Function

2020 ◽  
pp. 11-19 ◽  
Author(s):  
Fuad Al-Duais ◽  
Mohammed Alhagyan
Keyword(s):  
Weibull Distribution ◽  
Loss Function ◽  
Scale Parameter ◽  
Reliability Function ◽  
Record Values ◽  
Linex Loss Function ◽  
Asymmetric Loss ◽  
Bayes Estimates ◽  
Linex Loss ◽  
Asymmetric Loss Function

In this paper, we developed linear exponential (LINEX) loss function by emerging weights to produce weighted linear exponential (WLINEX) loss function. Then we utilized WLINEX to derive scale parameter and reliability function of the Weibull distribution based on record values when the shape parameter is known. After, we estimated scale parameter and reliability function of Weibull distribution by using maximum likelihood (ML) estimation and by several Bayes estimations.  The Bayes estimates were obtained with respect to symmetric loss function (squared error loss (SEL)), asymmetric loss function (LINEX) and asymmetric loss function (WLINEX). The ML and the different Bayes estimates are compared via a Monte Carlo simulation study. The result of simulation mentioned that the proposed WLINEX loss function is promising and can be used in real environment especially at the case of underestimate where it revealed better performance than LINEX loss function for estimating scale parameter.

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

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Fuad S. Al-Duais
Keyword(s):  
Bayesian Estimation ◽  
Loss Function ◽  
Likelihood Estimation ◽  
Reliability Function ◽  
Record Values ◽  
Linex Loss Function ◽  
Linex Loss ◽  
Upper Record Values ◽  
The Difference ◽  
Upper Record

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.

scholarly journals On estimation of gumbel type-ii with numerous kinds of linex loss function

2021 ◽  
Vol 1897 (1) ◽  
pp. 012008
Author(s):  
Nadia J. Fezaa Al-Obedy ◽  
Wafaa S. Hasanain
Keyword(s):  
Loss Function ◽  
Type Ii ◽  
Linex Loss Function ◽  
Linex Loss
Sign in / Sign up

Export Citation Format

Share Document