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# Hellinger distance based on mean and sd estimates of two normal distributions
H_normal <- function(mean1, sd1, mean2, sd2){
# the sd-part of the BC under normal approximation
# this part quantifies the spread modification
BC_normal_sd_part <- sqrt((2*sd1*sd2)/(sd1^2+sd2^2))
# the mean-part of the BC under normal approximation
# the mean-part is adjusted for standard deviations (it corresponds to the Mahalanobis distance)
# this part quantifies the location modification
BC_normal_mean_part <- exp(-((mean1-mean2)^2/(4*(sd1^2+sd2^2))))
# computation of the total BC under normality assumption
BC_normal_total <- BC_normal_sd_part * BC_normal_mean_part
## computation of the total Hellinger distance H under normality assumption
return(sqrt(1 - BC_normal_total))
}
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