Accession Number : AD0654460

Title :   ON ASYMPTOTICALLY ROBUST COMPETITORS OF THE ONE-SAMPLE T-TEST.

Descriptive Note : Technical rept.,

Corporate Author : JOHNS HOPKINS UNIV BALTIMORE MD DEPT OF STATISTICS

Personal Author(s) : Bloch,Daniel A. ; Gastwirth,Joseph L.

Report Date : MAR 1967

Pagination or Media Count : 16

Abstract : Although the t-test is one of the most commonly used statistical procedures, its behavior is somewhat sensitive to the assumption that the observations come from a normal distribution. Recently, it has been shown that 'quick estimators', i.e., estimators which are linear combinations of a few sample quantiles are robust estimators of the location parameter for a large class of symmetric unimodal densities. In order to use the median or any other 'quick estimator' as a test we must estimate its variance, or in large samples its asymptotic variance. The present paper is concerned with estimating (1/f squared) (nu subscript p) where nu subscript p is the true value of the p-th population quantile and f(x) is the density function. The estimator we consider has properties similar to those of Rosenblatt's estimate of a density function.

Descriptors :   (*STATISTICAL ANALYSIS, SAMPLING), MONTE CARLO METHOD, STATISTICAL TESTS, ERRORS, RANDOM VARIABLES, THEOREMS, PROBABILITY, MATHEMATICS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE