期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 48, 期 4, 页码 803-808出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.csda.2004.04.001
关键词
chi-square distribution; maximum absolute error; normal approximation; power transformation
An accurate normal approximation for the cumulative distribution function of the chi-square distribution with n degrees of freedom is proposed. This considers a linear combination of appropriate fractional powers of chi-square. Numerical results show that the maximum absolute error associated with the new transformation is substantially lower than that found for other power transformations of a chi-square random variable for all the degrees of freedom considered (1 less than or equal to 77 less than or equal to 1000). (C) 2004 Elsevier B.V. All rights reserved.
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