THE MONTE CARLO SIMULATION FOR ESTIMATING THE COEFFICIENTS OF SKEWNESS WHEN OBSERVATIONS ARE INVERSE GAUSSIAN DISTRIBUTED
Keywords:
Monte Carlo Simulation, Coefficients of Skewness, Inverse Gaussian DistributionAbstract
The objectives of this study are to propose the estimation method for coefficients of skewness of Inverse Gaussian data and to compare three estimation method for coefficients of skewness. Those methods are simple method, adjusted coefficients of skewness method with term (n-1)/n, and adjusted coefficients of skewness method with term (n-2)/n. The research was considered by the absolute bias (|Bias|) and the mean square errors (MSE). The comparisons were done by using sample sizes (n) equal to 10, 20, 30, 50 and 100 whereas parameter μ is 1 and parameters λ are 1, 3, 5, 10, 15, and 20. This research used the Monte Carlo simulation method. The experiment was repeated 10,000 times for each condition. Results of the research are as follows:
For all sample sizes and all parameter values, the |Bias| and the MSE of adjusted coefficients of skewness method with term (n-2)/n are the lowest. We can arrange the methods as follows: the adjusted coefficients of skewness method with term (n-1)/n and simple method, respectively.
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