การเปรียบเทียบประสิทธิภาพของการประมาณช่วงความเชื่อมั่นของพารามิเตอร์ ในการแจกแจงแกมมา A COMPARISON OF EFFICIENCY OF CONFIDENCE INTERVAL ESTIMATION OF PARAMETER ON GAMMA DISTRIBUTION
Keywords:
Gamma Distribution, Maximum Likelihood, Bayes’, Markov Chain Monte CarloAbstract
The objective of this research was to estimate the confidence interval of parameter ( ) on gamma distribution by using Maximum Likelihood (ML), Bayes’, and Markov Chain Monte Carlo (MCMC) methods. The efficient performance of these methods was considered by Confidence Coefficients (CC) and Average Width (AW). Therefore, the best estimation was the estimation, which having CC within the range of the fixed confidence interval, and having the lowest AW in each situation. The data was simulated from gamma distribution by setting the shape parameter ( ) as 2, 3, 4, 5, 6, 7, and 8, the scale parameter or called true parameter ( ) as 2, sample sizes ( ) as 30, 50, and 70, and the 95% and 99% confidence interval.
The results revealed that Bayes’ method showed the best performance in most all cases, except , . MCMC method had the efficient performance to estimate the confidence interval in some cases such as , and , at the 99% confidence interval. Maximum likelihood method was the lowest efficient method to estimate the confidence interval.
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