Borrajo García, María IsabelGonzález Manteiga, WenceslaoMartínez Miranda, María Dolores2019-11-282019-11-282017Borrajo, M. I., González-Manteiga, W., & Martínez-Miranda, M. D. (2017). Bandwidth selection for kernel density estimation with length-biased data. Journal of Nonparametric Statistics, 29(3), 636-668.1048-5252http://hdl.handle.net/10347/20313This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Nonparametric Statistics on 23 Jun 2017, available online: https://doi.org/10.1080/10485252.2017.1339309.Length-biased data are a particular case of weighted data, which arise in many situations: biomedicine, quality control or epidemiology among others. In this paper we study the theoretical properties of kernel density estimation in the context of length-biased data, proposing two consistent bootstrap methods that we use for bandwidth selection. Apart from the bootstrap bandwidth selectors we suggest a rule-of-thumb. These bandwidth selection proposals are compared with a least-squares cross-validation method. A simulation study is accomplished to understand the behaviour of the procedures in finite samplesengBootstrapRule-of-thumbCross-validationNonparametricWeighted datajournal article10.1080/10485252.2017.13393091029-0311open access