##' Calculates the LOO CV score for given data, regression prediction function and 'span'
##'
##' @param data   : regression data, a data.frame with columns 'x', 'y'
##' @param reg.fn : regr.prediction function ;  with arguments:
##'                       reg.x: regression x-values
##'                       reg.y: regression y-values
##'                       xout : x-value(s) of evaluation point(s)
##'                       span : smoothing parameter
##'                  value: prediction at the x-values  xout
##' @param span   : smoothing parameter, passed to reg.fn()
##' @return LOOCV score
loocv <- function(data, reg.fn, span)
{
  ## check arguments
  stopifnot(is.function(reg.fn), is.numeric(data$x), is.numeric(data$y),
            length(n <- length(data$x)) == 1, n >= 1)
  ## Calculate Leave-One-Out (LOO) regression values:
  loo.pred <- rep(NA, n)
  for(i in 1:n) {
      loo.pred[i] <- reg.fn(data$x[-i], data$y[-i], xout = data$x[i], span = span)
  }
  ## Calculate and return cv.MSE
  mean((data$y - loo.pred)^2)
}