On the relationship between two asymptotic expansions for the distribution of sample mean and its applications
The Annals of Statistics · 1997 · Volume 25 · Issue 5
Abstract
Although the cumulative distribution function may be differentiated to obtain the corresponding density function, whether or not a similar relationship exists between their asymptotic expansions remains a question. We provide a rigorous argument to prove that Lugannani and Rice's asymptotic expansion for the cumulative distribution function of the mean of a sample of i.i.d. observations may be differentiated to obtain Daniels's asymptotic expansion for the corresponding density function. We then apply this result to study the relationship between the truncated versions of the two series, which establishes the derivative of a truncated Lugannani and Rice series as an alternative asymptotic approximation for the density function. This alternative approximation in general does not need to be renormalized. Numerical examples demonstrating its accuracy are included.
Keywords
41A60, 62E20, asymptotic expansion, Daniels's series, Lugannani and Rice's series, saddlepoint approximation, uniform validity
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