Recently, a new procedure for distribution fitting, based on matching of the first two moments, partial and complete, was introduced (Shore, 1995). When the sampling skewness of the fitted distribution is compared to the sample skewness, and both are regarded as estimates of the skewness of the underlying distribution, the mean-squared-error of the former is appreciably lower than that of the latter. In this paper we present some simulation results to support this claim and demonstrate its magnitude An alternative two-moment distributional fitting procedure, based on a new family of four-parameter distributions, is also introduced and studied. Since three-moment distribution fitting is very common practice in simulation studies, these results may have important implications for the current state-of-the-art of simulation.
|Number of pages||12|
|Journal||Communications in Statistics Part B: Simulation and Computation|
|State||Published - 1 Jan 1996|
- Distribution fitting