This is the accepted version of the paper.This version of the publication may differ from the final published version. Hart and Sheather (2010a,b). We conclude that the slow convergence of data-driven bandwidths implies that once asymptotic theory is close to that of plug-in then it is the practical implementation that counts. This insight led us to a bandwidth selector search with the symmetrized version of onesided cross-validation as a clear winner. 1 Permanent repository link

This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent

The paper brings together the theory and practice of local linear kernel hazard estimation. Bandwidth selection is fully analysed, including double one-sided cross-validation that is shown to have good practical and theoretical properties. Insight is provided into the choice of the weighting function in the local linear minimization and it is pointed out that classical weighting sometimes lacks stability. A new semiparametric hazard estimator transforming the survival data before smoothing is introduced and shown to have good practical properties.

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