Title of article :
A note on efficient density estimators of convolutions
Author/Authors :
Bandyopadhyay، نويسنده , , Soutir Bandyopadhyay، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
It is already known that the convolution of a bounded density with itself can be estimated at the root-n rate using the two asymptotically equivalent kernel estimators: (i) Frees estimator (Frees, 1994) and (ii) Saavedra and Cao estimator (Saavedra and Cao, 2000). In this work, we investigate the efficiency of these estimators of the convolution of a bounded density. The efficiency criterion used in this work is that of a least dispersed regular estimator described in Begun et al. (1983). This concept is based on the Hájek–Le Cam convolution theorem for locally asymptotically normal (LAN) families.
Keywords :
Kernel Density , convolution , Locally asymptotically normal , Hellinger derivative
Journal title :
Journal of Statistical Planning and Inference
Journal title :
Journal of Statistical Planning and Inference