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 well-behaved 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