{
    huz <- deparse (substitute (x))
    x.mean <- mean (x)
    x.rel <- mean(x)/10 minimal binsize and
    max.rel <- x.mean
    binsize <- seq (x.rel, max.rel, by=x.rel)
    mat <- t(sapply (binsize, function (bz)
                     {
    hh <- tabulate (cut (x, seq(0, max (x), by=bz)))
    mat.mean <- mean (hh)
    mat.var <- var (hh)
    kleist <- c(mat.var, mat.mean)
}
                     )
             )
    mydata <- as.data.frame (mat)
    colnames (mydata) <- c("var", "mean")
     x.rel <- format (x.rel, digits = 2)
    max.rel <- format (max.rel, digits = 2)
    data.fit <- lm (log(var)~log(mean), data=mydata)
    alpha <- format (data.fit$coefficients[2], digits=4)
        r.quad <- format (summary (data.fit)$r.squared, digits=4)
    plot (log(var)~log(mean), data=mydata, main="Variance versus Mean", xlab="log mean", ylab="log variance")
    legend ("topleft",c(paste ("alpha", alpha, sep=" = "), paste("r2", r.quad, sep=" = "), paste ("min.bin", x.rel, sep=" = "), paste ("max.bin", max.rel, sep=" = "), paste ("steps", x.rel, sep=" = ")), bty="n")
    mtext (huz, side=3, cex=0.6)
    abline (data.fit, col="red")
}