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Neyman smooth goodness-of-fit tests for the marginal distribution of dependent data

✍ Scribed by Axel Munk; Jean-Pierre Stockis; Janis Valeinis; Götz Giese

Publisher: Springer Japan
Year: 2009
Tongue: English
Weight: 288 KB
Volume: 63
Category: Article
ISSN: 0020-3157
DOI: 10.1007/s10463-009-0260-2

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h l a n d Summuy A Neyman-type smooth teat ofgoodness of fit k derived for the geometric distribution. Some smellsample critical points are given, with two examples.