
Accession Number : ADA116167
Title : Rounding Error in Regression: The Appropriateness of Sheppard's Corrections.
Descriptive Note : Technical summary rept.,
Corporate Author : WISCONSIN UNIVMADISON MATHEMATICS RESEARCH CENTER
Personal Author(s) : Dempster,Arthur P ; Rubin,Donald B
PDF Url : ADA116167
Report Date : Apr 1982
Pagination or Media Count : 23
Abstract : We consider three simple approaches to rounding error in least squares regression. The first treats the rounded data as if they were unrounded, the second adds an adjustment to the diagonal of the covariance matrix of the variables, and the third subtracts an adjustment from the diagonal. The third, Sheppard's corrections, can be motivated as maximum likelihood with small rounding error and either (1) joint normal data or (2) normal residuals, regular independent variables, and large samples. Although an example and theory suggest that the third approach is usually preferable to the first two, a generally satisfactory attack on rounding error in regression requires the specification of the full distribution of variables, and convenient computational methods for this problem are not currently available. (Author)
Descriptors : *Regression analysis, *Least squares method, *Numerical methods and procedures, Covariance, Matrices(Mathematics), Sampling, Corrections, Variables, Distribution, Groups(Mathematics), Algorithms
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE