A minimum projected-distance test for parametric single-index Berkson models

Chuanlong Xie and Lixing Zhu ()
Additional contact information
Chuanlong Xie: Jinan University
Lixing Zhu: Hong Kong Baptist University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2018, vol. 27, issue 3, No 12, 700-715

Abstract: Abstract In this paper, we propose a minimum projected-distance test for parametric single-index regression models when the predictors are measured with Berkson errors. This test asymptotically behaves like a locally smoothing test as if the null model were with one-dimensional predictor, and is omnibus to detect all global alternative models. The test can also detect local alternative models that converge to the null model at the fastest rate that the existing locally smoothing tests with one-dimensional predictor can achieve. Therefore, the proposed test has potential for alleviating the curse of dimensionality in this field. We also give two bias-correction methods to center the test statistic. Numerical studies are conducted to examine the performance of the proposed test.

Keywords: Berkson model; Dimension reduction; Model checking; Parametric single-index model; 62F03; 62F05 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11749-017-0568-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:testjl:v:27:y:2018:i:3:d:10.1007_s11749-017-0568-9

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11749/PS2

DOI: 10.1007/s11749-017-0568-9

Access Statistics for this article

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Alfonso Gordaliza and Ana F. Militino

More articles in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().