Estimating Common Scale Parameter of Two Gamma Populations: A Simulation Study

2017 ◽  
Vol 36 (4) ◽  
pp. 346-362 ◽  
Author(s):  
Nadiminti Nagamani ◽  
Manas Ranjan Tripathy
Keyword(s):  
Simulation Study ◽  
Scale Parameter ◽  
Common Scale

scholarly journals Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution

2021 ◽  
Vol 19 (1) ◽  
pp. 2-21
Author(s):  
Talha Omer ◽  
Zawar Hussain ◽  
Muhammad Qasim ◽  
Said Farooq Shah ◽  
Akbar Ali Khan
Keyword(s):  
Simulation Study ◽  
Mean Squared Error ◽  
Scale Parameter ◽  
Rayleigh Distribution ◽  
Shrinkage Estimators ◽  
Unbiased Estimators ◽  
Squared Error ◽  
The Mean ◽  
Simulation Results

Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.

scholarly journals Classical and Bayesian Approach in Estimation of Scale Parameter of Nakagami Distribution

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Kaisar Ahmad ◽  
S. P. Ahmad ◽  
A. Ahmed
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimator ◽  
Bayesian Approach ◽  
Simulation Study ◽  
Bayesian Method ◽  
Scale Parameter ◽  
Loss Functions ◽  
Likelihood Estimator ◽  
R Software ◽  
Nakagami Distribution

Nakagami distribution is considered. The classical maximum likelihood estimator has been obtained. Bayesian method of estimation is employed in order to estimate the scale parameter of Nakagami distribution by using Jeffreys’, Extension of Jeffreys’, and Quasi priors under three different loss functions. Also the simulation study is conducted in R software.

Improved Estimation of the Common Scale Parameter of Several Pareto Distributions

1992 ◽  
Vol 42 (3-4) ◽  
pp. 177-190 ◽  
Author(s):  
Dipak K. De ◽  
Pei-San Liao Liu
Keyword(s):  
Scale Parameter ◽  
Minimum Variance ◽  
New Class ◽  
Numerical Studies ◽  
Pareto Distributions ◽  
Common Scale ◽  
Wage Distributions ◽  
Different Shapes ◽  
The Common ◽  
Improved Estimators

In this paper, we consider the estimation of the common scale parameter of several Pareto distributions with unknown and unequal shape parameters. This problem often arises in practice, for example, when we have several independent wage distributions each having a Pareto distribution with different shapes but common scale parameter which may be the minimum wage rate. A new class of improved estimators is obtained which dominates the Maximum Likelihood Estimator (MLE) and the Uniformly Minimum Variance Unbiased Estimators (UMVUE) under the Mean Square Error (MSE) and Pitman Nearness. (PN) criterion. Numerical studies indicate the amount of improvements are highly significant.

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