Baysbw: Local Bayesian function for bandwidth selection
In Disake: Discrete associated kernel estimators

Description Usage Arguments Details Value Author(s) References Examples

The function computes the optimal bandwidth using the local Bayesian approach.

1	Baysbw(Vec)

Vec

The data sample.

The Bayesian approach for variable bandwidth selection using Binomial kernel has been introduced by Zougab et al. (2012). The authors studied three Bayesian procedures to select the optimal bandwidth: the global, the local and the adaptive methods and they showed that the local procedure is better than the two others; see Zougab et al. (2013).

Returns the optimal bandwidth computed through local Bayesian procedure.

W. E. Wansouwé, C. C. Kokonendji and D. T. Kolyang

Zougab, N., Adjabi, S. and Kokonendji, C.C. (2012). Binomial kernel and Bayes local bandwidth in discrete functions estimation, Journal of Nonparametric Statistics 24, 783 - 795.

Zougab, N., Adjabi, S. and Kokonendji, C.C. (2013). A Bayesian approach to bandwidth selection in univariate associate kernel estimation, Journal of Statistical Theory and Practice 7, 8 - 23.

## Data can be simulated data or real data
## and bandwidth is computed through the local Bayesian procedure.
Vec<-c(10,0,1,0,4,0,6,0,0,0,1,1,1,2,4,4,5,6,6,6,6,7,1,7,0,7,7,
7,8,0,8,12,8,8,9,9,0,9,9,10,10,10,10,0,10,10,11,12,12,10,12,12,
13,14,15,16,16,17,0,12)
 
h_Bays<-Baysbw(Vec)