Accession Number : AD0665279

Title :   MINIMAX LINEAR PREDICTOR UNDER LIPSCHITZ' TYPE CONDITIONS FOR THE REGRESSION FUNCTION,

Corporate Author : NEW YORK UNIV N Y COURANT INST OF MATHEMATICAL SCIENCES

Personal Author(s) : Takeuchi,Kei

Report Date : JAN 1968

Pagination or Media Count : 43

Abstract : Regression analysis is one of the most popular and most often used techniques in various fields of statistical data analysis. In some cases, however, regression analysis is very dangerous, and sometimes gives awkward results. Such dangers, which are inherent in regression techniques, are well known, at least well perceived by experienced applied statisticians. But theoretical analysis of such a situation that yields some pitfalls to the careless application of regression analysis is far from satisfactory. Though well trained statisticians can evade such a danger by their good judgment, there is no formal well established technique that may be applied. The purpose of this paper is to derive some method to treat one such difficulty, i.e. the problem of the functional form of the regression.

Descriptors :   (*REGRESSION ANALYSIS, MATHEMATICAL PREDICTION), RANDOM VARIABLES, LEAST SQUARES METHOD, MINIMAX TECHNIQUE, TIME SERIES ANALYSIS, INTERPOLATION, APPROXIMATION(MATHEMATICS), NUMERICAL ANALYSIS, THEOREMS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE