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Bootstrap bandwidth selection method for local linear estimator in exponential family models

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  • K. Żychaluk

Abstract

Many biological experiments involve data whose distribution belongs to the exponential family. Such data are often analysed using generalised linear models but this method requires specification of the link function which can have strong influence on the resulting estimate. Instead a local method based on quasi-likelihood can be used, but the choice of the smoothing parameter is crucial for its performance. A bootstrap bandwidth selection method is proposed and shown to be consistent. Examples of application to data from biological and psychometric experiments are given.

Suggested Citation

  • K. Żychaluk, 2014. "Bootstrap bandwidth selection method for local linear estimator in exponential family models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(2), pages 305-319, June.
    • Handle: RePEc:taf:gnstxx:v:26:y:2014:i:2:p:305-319
    DOI: 10.1080/10485252.2014.885023
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    References listed on IDEAS

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    1. Cao, R., 1993. "Bootstrapping the Mean Integrated Squared Error," Journal of Multivariate Analysis, Elsevier, vol. 45(1), pages 137-160, April.
    2. Heiler, Siegfried & Feng, Yuanhua, 1997. "A bootstrap bandwidth selector for local polynomial fitting," Discussion Papers, Series II 344, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    3. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
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