#
# Written by:
# -- 
# John L. Weatherwax                2009-04-21
# 
# email: wax@alum.mit.edu
# 
# Please send comments and especially bug reports to the
# above email address.
#
#-----

median_smoothed_bootstrap = function(data, B=100, h=1){
    #
    # Code derived from pseudocode on Page 90 from Good's book.
    # 
    # h is a kernel smoothing parameter.
    #
    # This is my best estimate of what that code should be given that
    # it seems like there are typos in the books discussion of this algorithm.
    #
    n = length(data) # the number of data points in the original sample
    boot_medians = rep( NA, B )

    for( bi in 1:B ){
        xb = sample( data, length(data), replace=TRUE )
        xb_mean = mean( xb )
        xb_std = sd( xb )

        boot_sample = xb_mean + ( xb - xb_mean + h * rnorm(n) ) / sqrt( 1 + (h / xb_std)^2 )
        boot_medians[bi] = median( boot_sample )
    }
    return( boot_medians )
}