R/loessWrapperMod.R

In adductomicsR: Processing of adductomic mass spectral datasets

#' wrapper script for loess modeling
#' @description adapted from bisoreg package
#' @param x predictor values
#' @param y response values
#' @param span.vals values of the tuning parameter to evaluate
#' using cross validation
#' @param folds number of 'folds' for the cross-validation procedure
#' @examples loessWrapperMod (rnorm(200), rnorm(200), span.vals =
#' seq(0.25, 1, by = 0.05),folds = 5)
#' @return LOESS model
#' @usage loessWrapperMod(x, y, span.vals = seq(0.25, 1, by = 0.05),
#' folds = 5)
#' @export
loessWrapperMod <-
    function(x,
            y,
            span.vals = seq(0.25, 1, by = 0.05),
            folds = 5) {
        mae <- numeric(length(span.vals))
        theta.fit <- function(x, y, span)
            loess(y ~ x, span = span,
                surface = "direct")
        theta.predict <- function(fit, x0)
            predict(fit, newdata = x0)
        ii = 0
        for (span in span.vals) {
            ii <- ii + 1
            y.cv <- bootstrap::crossval(x,
                                        y,
                                        theta.fit,
                                        theta.predict,
                                        span = span,
                                        ngroup = folds)$cv.fit
            fltr <- !is.na(y.cv)
            mae[ii] <- mean(abs(y[fltr] - y.cv[fltr]))
        }
        span <- span.vals[which.min(mae)]
        out <- loess(y ~ x, span = span, surface = "direct")
        return(out)
    }