From ba98a0b27361cb0987fb8c911d256dd1c919f269 Mon Sep 17 00:00:00 2001 From: Thibaut Horel Date: Tue, 7 Feb 2012 16:11:47 -0800 Subject: Analysis of the submodularity with quadratic form theory. Add a paper from Richardson on LSE. --- notes.bib | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) (limited to 'notes.bib') diff --git a/notes.bib b/notes.bib index 785cf1e..db41d54 100644 --- a/notes.bib +++ b/notes.bib @@ -149,3 +149,22 @@ year={1950}, publisher={JSTOR} } + +@article{lse, + jstor_articletype = {research-article}, + title = {Least Squares and Grouping Method Estimators in the Errors in Variables Model}, + author = {Richardson, David H. and Wu, De-Min}, + journal = {Journal of the American Statistical Association}, + jstor_issuetitle = {}, + volume = {65}, + number = {330}, + jstor_formatteddate = {Jun., 1970}, + pages = {pp. 724-748}, + url = {http://www.jstor.org/stable/2284583}, + ISSN = {01621459}, + abstract = {The probability density function of the least squares estimator of the slope coefficient in the errors in variables model is presented. It is shown how the bias and mean-square error of the least squares estimator b depend on the parameters of the model. In particular, for a given sample size, b converges to the true parameter as one of the distribution parameters increased indefinitely. The analysis is supplemented with numerical computations of the relative bias and mean-square error. The distribution function of the grouping method estimator b̄ has the same form as that of b. The biases and mean-square errors of b and b̄ are compared. For the case of zero within-group variance, the use of b̄ always reduces the magnitude of the relative bias and generally reduces the mean-square error. For large values of the within-group variance, use of b̄ may result in an increase in mean-square error.}, + language = {English}, + year = {1970}, + publisher = {American Statistical Association}, + copyright = {Copyright © 1970 American Statistical Association}, + } -- cgit v1.2.3-70-g09d2