Tail behavior of the least-squares estimator
The tail behavior of the least-squares estimator in the linear regression model was studied in He et al. (Econometrica 58 (1990) 1195) under a fixed design for finite n. We now consider a random design matrix Xn and the case n-->[infinity] and study the probability with [gamma]n=F-1(1-1/n), a population analog of the maximal error. Unlike in the situation with fixed n and [gamma]-->[infinity], for n-->[infinity] we find fairly good tail behavior of LSE for normal F, for both fixed and random designs, even under heavy-tailed distribution for Xn.
Volume (Year): 55 (2001)
Issue (Month): 4 (December)
|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|
References listed on IDEAS
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.:
- He, Xuming, et al, 1990. "Tail Behavior of Regression Estimators and Their Breakdown Points," Econometrica, Econometric Society, vol. 58(5), pages 1195-1214, September.
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:55:y:2001:i:4:p:377-384. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.