Bayesian estimation based on ranked set sample from Morgenstern type bivariate exponential distribution when ranking is imperfect

Metrika ◽  
2016 ◽  
Vol 80 (3) ◽  
pp. 333-349
Author(s):  
Manoj Chacko
Keyword(s):  
Bayesian Estimation ◽  
Exponential Distribution ◽  
Bivariate Exponential Distribution ◽  
Ranked Set Sample ◽  
Bivariate Exponential

An Improved Estimation of Parameter of Morgenstern-Type Bivariate Exponential Distribution Using Ranked Set Sampling

2022 ◽  
pp. 1-25
Author(s):  
Vishal Mehta
Keyword(s):  
Exponential Distribution ◽  
Mean Squared Error ◽  
Ranked Set Sampling ◽  
Error Estimator ◽  
Bivariate Exponential Distribution ◽  
Ranked Set Sample ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Bivariate Exponential ◽  
Special Cases

In this chapter, the authors suggest some improved versions of estimators of Morgenstern type bivariate exponential distribution (MTBED) based on the observations made on the units of ranked set sampling (RSS) regarding the study variable Y, which is correlated with the auxiliary variable X, where (X,Y) follows a MTBED. In this chapter, they firstly suggested minimum mean squared error estimator for estimation of 𝜃2 based on censored ranked set sample and their special case; further, they have suggested minimum mean squared error estimator for best linear unbiased estimator of 𝜃2 based on censored ranked set sample and their special cases; they also suggested minimum mean squared error estimator for estimation of 𝜃2 based on unbalanced multistage ranked set sampling and their special cases. Efficiency comparisons are also made in this work.

BLOCK AND BASU'S BIVARIATE EXPONENTIAL DISTRIBUTION WITH APPLICATION TO DROUGHT DATA

2006 ◽  
Vol 21 (1) ◽  
pp. 143-155 ◽  
Author(s):  
Saralees Nadarajah ◽  
Samuel Kotz
Keyword(s):  
Exponential Distribution ◽  
Bivariate Exponential Distribution ◽  
Bivariate Exponential ◽  
Exact Distributions ◽  
Hydrological Applications

Motivated by hydrological applications, the exact distributions ofR=X+Y,P=XY, andW=X/(X+Y) and the corresponding moment properties are derived whenXandYfollow Block and Basu's bivariate exponential distribution. An application of the results is provided to drought data from Nebraska.

Predicting the Duration of Manufacturing Process with Two Complement Materials

2016 ◽  
Vol 709 ◽  
pp. 46-50
Author(s):  
Hui Hsin Huang
Keyword(s):  
Exponential Distribution ◽  
Future Study ◽  
Manufacturing Process ◽  
Bivariate Exponential Distribution ◽  
Moment Methods ◽  
Bivariate Exponential ◽  
The Future ◽  
Production Demand

In the marketing, there are some correlated between two complement materials when predicting the duration of manufacturing process. Two different kinds of materials are complementary if using more of one material requires the use of more of another. Thus, based on this view of point, when we estimate the production demand quantity, we can’t consider these two durations of manufacturing process as dependent. In this paper we propose the bivariate exponential distribution to model two related manufacturing durations of two complement materials. Finally, we demonstrate both MLE and moment methods to estimate the parameters of our model. This can provide the reference for the future study to choice a suitable estimation.

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