On testing independence with right truncated data
dc.citation.epage | 3206 | en_US |
dc.citation.issueNumber | 5 | en_US |
dc.citation.spage | 3201 | en_US |
dc.citation.volumeNumber | 30 | en_US |
dc.contributor.author | Gurler, U. | en_US |
dc.date.accessioned | 2015-07-28T11:56:28Z | |
dc.date.available | 2015-07-28T11:56:28Z | |
dc.date.issued | 1997-12 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | Inference with bivariate data gained considerable interest recently, See eg.[1],[10],[12]. All of these studies howrver consider estimation of the bivariate distribution function under various bivariate censoring models. Recently (:iirler[7,8] considered estimation of the bivariate distribution and the hazard functions under trunc.atlon/censoring models. The purpose of this study is to investigate procedures for testing the independence of I hc components of the bivariate vector for truncated data. To this end, further properties of the bivariate functrouals introduced in GiirleQ] are elaborated. Two alternative methods for hypothesis testing are suggested aud some large sample properties are derived. The procedures suggested in this paper are applicable to left/right. truncated and left truncated right censored data. However to keep the presentation simple we ~~oufinr t.hr discussion to the right truncated case. Also, to avoid technicalities, it is assumed that all the univariat.e and the bivariate distribution functions are absolutely continuous admitting densities. | en_US |
dc.description.provenance | Made available in DSpace on 2015-07-28T11:56:28Z (GMT). No. of bitstreams: 1 10.1016-S0362-546X(97)00414-8.pdf: 293380 bytes, checksum: 1afaee84255e842e7cd869d0929ef3cb (MD5) | en |
dc.identifier.doi | 10.1016/S0362-546X(97)00414-8 | en_US |
dc.identifier.issn | 0362-546X | |
dc.identifier.uri | http://hdl.handle.net/11693/10990 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/S0362-546X(97)00414-8 | en_US |
dc.source.title | Nonlinear Analysis: Theory, Methods and Applications | en_US |
dc.subject | Right Truncation | en_US |
dc.subject | Test Of Independence | en_US |
dc.subject | Reverse Hazard | en_US |
dc.subject | Nonparametric Estimation | en_US |
dc.title | On testing independence with right truncated data | en_US |
dc.type | Article | en_US |
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