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A Viable Alternative to Resorting to Statistical Tables
Authors:Hyung-Tae Ha  Serge B Provost
Institution:1. Department of Applied Statistics , Kyungwon University , Sung-Nam, South Korea htha@kyungwon.ac.kr;3. Department of Statistical &4. Actuarial Sciences , The University of Western Ontario , London, Ontario, Canada
Abstract:It is shown in this article that, given the moments of a distribution, any percentage point can be accurately determined from an approximation of the corresponding density function in terms of the product of an appropriate baseline density and a polynomial adjustment. This approach, which is based on a moment-matching technique, is not only conceptually simple but easy to implement. As illustrated by several applications, the percentiles so obtained are in excellent agreement with the tabulated values. Whereas statistical tables, if at all available or accessible, can hardly ever cover all the potentially useful combinations of the parameters associated with a random quantity of interest, the proposed methodology has no such limitation.
Keywords:Approximate distributions  Computational statistics  Moments  Percentage points  Percentiles  p-values  Statistical tables
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