### Name: empinf
### Title: Empirical Influence Values
### Aliases: empinf
### Keywords: nonparametric math

### ** Examples

# The empirical influence values for the ratio of means in
# the city data.
ratio <- function(d, w) sum(d$x *w)/sum(d$u*w)
empinf(data=city,statistic=ratio)
city.boot <- boot(city,ratio,499,stype="w")
empinf(boot.out=city.boot,type="reg")

# A statistic that may be of interest in the difference of means
# problem is the t-statistic for testing equality of means.  In
# the bootstrap we get replicates of the difference of means and
# the variance of that statistic and then want to use this output
# to get the empirical influence values of the t-statistic.
grav1 <- gravity[as.numeric(gravity[,2])>=7,]
grav.fun <- function(dat, w)
{    strata <- tapply(dat[, 2], as.numeric(dat[, 2]))
     d <- dat[, 1]
     ns <- tabulate(strata)
     w <- w/tapply(w, strata, sum)[strata]
     mns <- tapply(d * w, strata, sum)
     mn2 <- tapply(d * d * w, strata, sum)
     s2hat <- sum((mn2 - mns^2)/ns)
     c(mns[2]-mns[1],s2hat)
}

grav.boot <- boot(grav1, grav.fun, R=499, stype="w", strata=grav1[,2])

# Since the statistic of interest is a function of the bootstrap
# statistics, we must calculate the bootstrap replicates and pass
# them to empinf using the t argument.
grav.z <- (grav.boot$t[,1]-grav.boot$t0[1])/sqrt(grav.boot$t[,2])
empinf(boot.out=grav.boot,t=grav.z)