Compute/plot a weighted histogram using base graphics.

weighted.histogram.R

weighted.histogram <-
function() {
    cl <- match.call()
    cl$w <- NULL
    cl[[1L]] <- as.name("hist.default")
    cl$plot <- FALSE
    h <- eval.parent(cl)
    f <- factor(findInterval(x, h$breaks, left.open = TRUE,
        rightmost.closed = TRUE,
        all.inside = TRUE),
        levels = seq.int(length(h$breaks) - 1L))
    y <- tapply(w, f, sum, na.rm = TRUE)
    y[is.na(y)] <- 0
    h$counts <- y * length(f)
    h$density <- y / diff(h$breaks)
    if (plot) {
        if (is.null(freq)) 
            freq <- if (!missing(probability))
                !as.logical(probability) else h$equidist
        breaks <- h$breaks
        xname <- h$xname
        plot(h, freq = freq, col = col, border = border, angle = angle, 
            density = density, main = main, xlim = xlim, ylim = ylim, 
            xlab = xlab, ylab = ylab, axes = axes, labels = labels, 
            ...)
        invisible(h)
    } else h
}
formals(weighted.histogram) <-
append(formals(hist.default), alist(w = ), after = 1)
formals(weighted.histogram)['main'] <- alist(paste("Weighted histogram of", xname))

This function modifies hist.default by adding a weights argument (w, 2-nd position). The usage is as in hist.default.

x <- rpois(100, 10)
wts <- runif(100)
par(mfrow = c(1,2))
hist(x)
weighted.histogram(x, wts)