Mean squared error of James–Stein estimators for measurement error models
Whittemore (1989) in an interesting paper considered estimation of regression coefficients in measurement error models. She had the very interesting result which showed how to overcome the inconsistency of the usual least squares estimator of the regression coefficient in a measurement error model by an alternative James–Stein (James and Stein, 1961) estimator. The author did not provide a rigorous proof for the consistency of the suggested estimator, nor did she provide MSE of her estimator. Our objective is to provide a rigorous second order expansion of the mean squared error of the proposed James–Stein estimator under both known measurement variance and unknown measurement variance.
Volume (Year): 82 (2012)
Issue (Month): 11 ()
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- H. Schneeweiß, 1976. "Consistent estimation of a regression with errors in the variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 23(1), pages 101-115, December.
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:82:y:2012:i:11:p:2033-2043. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.