Framework and Case Study for Optimizing Target Value of a Process Using Taguchi’s Asymmetric Loss Function

Author(s):  
Anoop Pandey ◽  
Manish Chaturvedi
2013 ◽  
Vol 28 (2) ◽  
pp. 333-343 ◽  
Author(s):  
Ulrich Fritsche ◽  
Christian Pierdzioch ◽  
Jan-Christoph Rülke ◽  
Georg Stadtmann

Author(s):  
Fuad Al-Duais ◽  
Mohammed Alhagyan

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.


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