
Accession Number : AD0717937
Title : Nonparametric Estimation of Mean and Variance When a Few 'Sample' Values Possibly Outliers.
Descriptive Note : Technical rept.,
Corporate Author : SOUTHERN METHODIST UNIV DALLAS TEX DEPT OF STATISTICS
Personal Author(s) : Walsh,John E.
Report Date : 18 DEC 1970
Pagination or Media Count : 9
Abstract : The data (continuous) are n independent observations that are believed to be a random sample. The possibility exists, however, that as many as J of the largest observations, and as many as K of the smallest observations, are outliers. That is, these observations are from populations that are different from the population yielding the other observations (which number at least n  J  K). The interest is in obtaining suitable estimates for the mean and variance of the population yielding the other observations. J and K are given and relatively small, with both = or < 2(n sup A), where A is specified and = or < 1/4. When the population yielding the other observations is continuous, has moments of all orders, and is wellbehaved in some other ways, estimates are developed that are unbiased if term of order n sup (1+A+2 epsilon) are neglected. Here, epsilon can be arbitrarily small but is positive. (Author)
Descriptors : (*STATISTICAL DISTRIBUTIONS, ANALYSIS OF VARIANCE), MATHEMATICAL PREDICTION, SAMPLING
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE