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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.
Acknowledgements
I thank A.W. Bowman and D.H. Foster for useful discussion. I am also grateful to N. P. Cooper and A. J. Schofield for making available unpublished data and to A.W. Bowman, D.H. Foster and P.N. Patil for critically reading the manuscript. I am also indebted to I.C. Smith for help in using the High Throughput Computing Condor at University of Liverpool. This work was supported by the EPSRC (Grant No. EP/C003470/1).