Estimation and test of linearity for a class of additive nonlinear models

Nathalie Chèze-Payaud, Jean-Michel Poggi and Bruno Portier

Statistics & Probability Letters, 1998, vol. 40, issue 2, 189-201

Abstract: This paper deals with the estimation and the test for linearity of models belonging to a class of additive nonlinear ones. We prove the joint asymptotic normality for a kernel estimator and provide a test for linearity of each function defining the model.

Keywords: Nonlinear; additive; models; Test; for; linearity; Kernel; estimates (search for similar items in EconPapers)
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(98)00113-8
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:40:y:1998:i:2:p:189-201

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 ().