R/normalize.xdate.R

In AndyBunn/dplR: Dendrochronology Program Library in R

normalize.xdate <- function(rwl, series, n, prewhiten, biweight,
                            leave.one.out = FALSE) {
    loo <- isTRUE(leave.one.out)
    ## Run hanning filter over the data if n isn't NULL
    ## divide by mean if n is null
    if(is.null(n)){
        master.stats <- colMeans(rwl, na.rm=TRUE)
        master.df <- sweep(rwl, 2, master.stats, "/")
        if (!loo) {
            series.out <- series / mean(series, na.rm=TRUE)
        }
    } else {
        master.stats <- apply(rwl, 2, hanning, n)
        master.df <-  rwl / master.stats
        if (!loo) {
            series.out <- series / hanning(series, n)
        }
    }
    if (loo) {
        nseries <- ncol(rwl)
        ## Apply ar if prewhiten
        if(prewhiten){
            ## mark any columns without at least four observations
            goodCol <- colSums(!is.na(master.df)) > 3
            series.out <-  apply(master.df, 2, ar.func)
        } else {
            goodCol <- rep.int(TRUE, nseries)
            series.out <- master.df
        }
        master <- series.out
        if (!biweight) {
            for (i in seq_len(nseries)) {
                goodCol2 <- goodCol
                goodCol2[i] <- FALSE
                master[, i] <-
                    rowMeans(series.out[, goodCol2, drop = FALSE], na.rm=TRUE)
            }
        } else {
            for (i in seq_len(nseries)) {
                goodCol2 <- goodCol
                goodCol2[i] <- FALSE
                master[, i] <-
                    apply(series.out[, goodCol2, drop = FALSE], 1, tbrm, C = 9)
            }
        }
    } else {
        ## Apply ar if prewhiten
        if(prewhiten){
            ## drop any columns without at least four observations
            master.df <- master.df[, colSums(!is.na(master.df)) > 3, drop=FALSE]
            master.df <-  apply(master.df, 2, ar.func)
            series.out <- ar.func(series.out)
        }

        if (!biweight) master <- rowMeans(master.df, na.rm=TRUE)
        else master <- apply(master.df, 1, tbrm, C = 9)
    }
    list(master=master, series=series.out)
}