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  • 标题:Multinomial goodness–of–fit: Large–sample tests with survey design correction and exact tests for small samples
  • 本地全文:下载
  • 作者:Jann, Ben
  • 期刊名称:Journal of Food Distribution Research
  • 印刷版ISSN:0047-245X
  • 出版年度:2008
  • 卷号:39
  • 期号:SUPPL
  • 页码:147-169
  • 出版社:Food Distribution Research Society
  • 摘要:I introduce the new mgof command to compute distributional tests for discrete (categorical, multinomial) variables. The command supports largesample tests for complex survey designs and exact tests for small samples as well as classic large-sample x2-approximation tests based on Pearson’s X2, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read, 1984, Journal of the Royal Statistical Society, Series B (Methodological) 46: 440–464). The complex survey correction is based on the approach by Rao and Scott (1981, Journal of the American Statistical Association 76: 221–230) and parallels the survey design correction used for independence tests in svy: tabulate. mgof computes the exact tests by using Monte Carlo methods or exhaustive enumeration. mgof also provides an exact one-sample Kolmogorov–Smirnov test for discrete data.
  • 关键词:mgof;mgofi;multinomial;goodness-of-fit;chi-squared;categorical data;exact tests;Monte Carlo;exhaustive enumeration;combinatorial algorithms;complex survey correction;power-divergence statistic;Kolmogorov–Smirnov;Benford's law
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