On the asymptotic power of a goodness-of-fit test based on a cumulative Kullback-Leibler discrepancy

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• 作者：A. Contreras-Cristá ; n^a ; ^{alberto@sigma.iimas.unam.mx" class="auth_mail" title="E-mail the corresponding author} ; E. Gutié ; rrez-Pe&ntilde ; a^a ; S.G. Walker^b
• 关键词：EDF statistic ; Information measure ; Power of a test
• 刊名：Statistics & Probability Letters
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：120
• 期：Complete
• 页码：118-125
• 全文大小：410 K

文摘

We discuss a goodness-of-fit test arising from information-theoretical considerations. We show that, for a simple null hypothesis, our test has superior asymptotic power compared to the Anderson–Darling test when the alternative lies in a certain large class of distribution functions.