Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/28357
Title: | Nonparametric estimation of the cross ratio function | Authors: | ABRAMS, Steven JANSSEN, Paul SWANEPOEL, Jan VERAVERBEKE, Noel |
Issue Date: | 2020 | Publisher: | SPRINGER HEIDELBERG | Source: | Annals of the Institute of Statistical Mathematics, 72 (3), p. 771-801 | Abstract: | The cross ratio function (CRF) is a commonly used tool to describe local dependence between two correlated variables. Being a ratio of conditional hazards, the CRF can be rewritten in terms of (first and second derivatives of) the survival copula of these variables. Bernstein estimators for (the derivatives of) this survival copula are used to define a nonparametric estimator of the cross ratio, and asymptotic normality thereof is established. We consider simulations to study the finite sample performance of our estimator for copulas with different types of local dependency. A real dataset is used to investigate the dependence between food expenditure and net income. The estimated CRF reveals that families with a low net income relative to the mean net income will spend less money to buy food compared to families with larger net incomes. This dependence, however, disappears when the net income is large compared to the mean income. | Keywords: | Asymptotic distribution;Bernstein estimation;Copula;Cross ratio function;Hazard rate | Document URI: | http://hdl.handle.net/1942/28357 | ISSN: | 0020-3157 | e-ISSN: | 1572-9052 | DOI: | 10.1007/s10463-019-00709-3 | ISI #: | 000528606800006 | Rights: | The Institute of Statistical Mathematics, Tokyo 2019. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
CRF_aism_D1700229R2_final_version.pdf | Peer-reviewed author version | 755.19 kB | Adobe PDF | View/Open |
Nonparametric estimation of the cross ratio function.pdf Restricted Access | Published version | 700.41 kB | Adobe PDF | View/Open Request a copy |
WEB OF SCIENCETM
Citations
3
checked on Mar 23, 2024
Page view(s)
138
checked on Jun 24, 2022
Download(s)
210
checked on Jun 24, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.