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scacum <- structure(function#Cummulative-scaled sums
### This function computes cummulative and scaled sums of time-series
### replicates.
##details<< Cummulative sums of time-series
## replicates (e.g. tree-ring widths) are scaled
## around reference values (e.g. tree radii).
(
x, ##<<\code{numeric} vector of time-series replicates with names
##of the vector being time units.
sc.c = NA, ##<<\code{numeric} constant. Scaling constant. If
##\code{NA} then the computed cumulative sums are not
##scaled.
rf.t = NA ##<<\code{NA}, or \code{numeric} constant. Reference
##time of the scaling constant. If \code{NA} then
##maximum time in vector-name range is used.
) {
csn. <- FALSE
if(is.data.frame(x)){
csnu <- cClass(x, 'numeric')
csn <- c(cClass(x, 'integer'), cClass(x, 'factor'))
csn. <- length(csn)!=0
csn.. <- csn[!csn%in%'csx']
cd <- x
x <- x[,'x']
names(x) <- cd[,'year']}
if(is.null(names(x)))
stop('NULL labels in x', call. = FALSE)
xcum <- cumsum(x)
if(is.na(rf.t))
rf.t <- max(as.numeric(names(x)))
inc <- 0
if(!is.na(sc.c))
inc <- sc.c - xcum[as.character(rf.t)]
csx <- xcum + inc
if(any(csx < 0,na.rm = TRUE))
csx <- xcum
xd <- data.frame(x,csx)
if(csn.&& length(csnu) > 1){
xd <- cd[,csnu]
xd[,'csx'] <- csx }
if(csn.)
xd <- cbind(xd,cd[,csn..])
return(xd)
### data frame with the original vector, and its scaled-cummulative sums.
} , ex=function() {
x <- c(0.79,0.32,0.53,0.43,0.18)
names(x) <- 1948:1952
scacum(x,sc.c = 4,rf.t = 1951)
##If sc.c = NA then cummulative values are scaled arround
##max(cumsum(x)):
max(cumsum(x))
scacum(x,NA,1951)
})
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