Publications and Preprints

Smoothing Parameter Selection for Nonparametric Density Estimation for Length-biased Data: A Bayesian Perspective
Yogendra P. Chaubey, Jun Li and Isha Dewan
Nonparametric estimation of densities defined over non-negative observations using asymmetric kernels is of special interest as it has potential to remove the spill-over effect at the boundary. One important problem in this context is the selection of the smoothing parameter. The purpose of the this note is to review some recent work on the application of Bayes criterion for this purpose and investigate its application in the context of length biased data.

isid/ms/2015/01 [fulltext]

Click here to return to Preprints Page