An Efficiency of Interval Estimation for Continuous Variable by Jackknifing and Bootstrapping Method
Keywords:
Jackknifing, Bootstrapping, Parameter estimation, Confidence intervalAbstract
The purpose of this study was to compare the efficiency of interval estimation mean, variance, skewness and kurtosis of continuous variable between Jackknifing and Bootstrapping method. Data are generated using Monte Carlo Simulation Technique by R-Program. Standard normal distribution, t-distribution, exponential distribution, and gamma distribution were generated at the sample of size 100, 200, 300, 400 and 500 at significance levels of 0.01 and 0.05. In each situation data was simulated and repeated 1,000 times. The efficiency was considered by confidence coefficient of the interval estimation. The results showed that Bootstrapping method gave the higher confidence coefficient than Jackknifing method in four parameters of each distribution. Therefore, Bootstrapping method was more efficient than Jackknifing method.
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References
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