Spiking problem in monotone regression: Penalized residual sum of squares

Jayanta Kumar Pal

Statistics & Probability Letters, 2008, vol. 78, issue 12, 1548-1556

Abstract: We consider the estimation of a monotone function at its end-point, where the least square estimate is inconsistent. The least square criterion is penalized to achieve consistency. The limit distribution for the residual sum of squares is derived, to construct confidence intervals.

Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(08)00010-2
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:78:y:2008:i:12:p:1548-1556

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 ().