Implementation of Upper Multinomial Bound Using Clustering

作者: Robert A. Leitch , John Neter , Robert Plante , Prabhakant Sinha

DOI: 10.1080/01621459.1981.10477680

关键词: Biological sciencesCombinatoricsStatisticsCluster analysisSample (statistics)MathematicsMultinomial distributionZero (linguistics)PopulationNonparametric statistics

摘要: Abstract The multinomial bound is a nonparametric for finite population total when most elements have value of zero and the remaining positive values, such as occur in accounting threshold problems physical biological sciences. Up to now, computational difficulties restricted use cases where sample contains eight or less errors. clustered errors described this paper extends up 25 errors, with only moderate loss tightness bound.

参考文章(4)
Walter D. Fisher, On Grouping for Maximum Homogeneity Journal of the American Statistical Association. ,vol. 53, pp. 789- 798 ,(1958) , 10.1080/01621459.1958.10501479
Stephen E. Fienberg, John Neter, R. A. Leitch, Estimating the Total Overstatement Error in Accounting Populations Journal of the American Statistical Association. ,vol. 72, pp. 295- 302 ,(1977) , 10.1080/01621459.1977.10480993
D. R. COX, E. J. SNELL, On sampling and the estimation of rare errors Biometrika. ,vol. 66, pp. 125- 132 ,(1979) , 10.1093/BIOMET/66.1.125