On necessary conditions for the weak consistency of minimum L1-norm estimates in linear models
Z. D. Bai and
Y. Wu
Statistics & Probability Letters, 1997, vol. 34, issue 2, 193-199
Abstract:
Consider the model yi = x'i[beta]0 + ei, I = 1,...,n. Under very weak conditions on the error distributions, it is shown that is a necessary conditions for the weak consistency of a minimum L1-norm estimate of [beta]0, which cannot be further improved.
Keywords: Minimum; L1; norm; estimate; Weak; consistency; Linear; regression; model; Necessary; condition (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(96)00182-4
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:34:y:1997:i:2:p:193-199
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().