Stochastic Regression with Errors in Both Variables

Article

Gunst, Richard F.; Lakshminarayanan, Mani Y.; Reilman, Miriam A.   (1986, ASQC)   Southern Methodist University; University of South Alabama

Journal of Quality Technology    Vol. 18    No. 3
QICID: 5549    July 1986    pp. 162-169
List $10.00
Member $5.00

FOR A LIMITED TIME, ACCESS TO THIS CONTENT IS FREE!
You will need to be signed in.
New to ASQ? Register here.

Article Abstract

Linear structural models are linear relationships between two stochastic (random) variates in which both of the variates are subject to measurement errors. Structural models are common in experimental work, but are typically fit using least squares. In this expository paper maximum likelihood estimators for linear structural models are presented and contrasted with the corresponding least squares estimators. Asymptotic variance formulae for the intercept and slope estimators are given, along with the corresponding expressions for linear functional models.

Keywords

Regression,Calibration,Least squares,Maximum likelihood estimate (MLE),Measurement error


Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers





ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.