Shubha,
I apologize if this is a bit late - consequence of digest summary preference.
If I understand what you need, it is to calculate the value at month
end given a data object. For zoo objects the following should do what
you need. Actually is part of my new package on CRAN quantmod -
basically a workflow management tool for quant finance modelling.
Also visible at www.quantmod.com
If you convert your data.frame to a zoo object (designed for ordered
obs. - e.g. time-series)
# for your data - which I don't know : )
zoo.ts <- zoo(youdataframe[,-1],as.Date(yourdataframe[,1]))
# ^
^
# ^ ^
^ ^
# minus 'date' column the 'date'
column - in CCYY-MM-DD format
My example:
A zoo time series object consisting of 231 days:
> zoo.ts <- zoo(rnorm(231),as.Date(13514:13744))
> start(zoo.ts)
[1] "2007-01-01"
> end(zoo.ts)
[1] "2007-08-19"
# these are the end points of each period
> breakpoints(zoo.ts,months,TRUE)
[1] 0 31 59 90 120 151 181 212 231
# get the associated values
> zoo.ts[breakpoints(zoo.ts,months,TRUE)]
2007-01-31 2007-02-28 2007-03-31 2007-04-30 2007-05-31 2007-06-30
-0.008829668 -2.207802921 0.171705151 -1.820125167 1.776643162 0.884558259
2007-07-31 2007-08-19
0.655305543 0.191870144
You can also apply a function inside each of these periods (intervals)
with the function
period.apply:
e.g. the standard deviation of each period would be had with:
> period.apply(zoo.ts,breakpoints(zoo.ts,months,TRUE),FUN=sd)
[1] 0.9165168 1.2483743 1.0717529 1.2002236 0.9568443 0.8112068 0.8563814
[8] 0.8671502
The functions (and many others) are in quantmod - on CRAN and most up
to date at www.quantmod.com
For those who'd rather just have the functions:
breakpoints <-
function (x, by = c(weekdays, weeks, months, quarters, years), ...)
{
if (length(by) != 1)
stop("choose ONE method for \"by\"")
by <- match.fun(by)
breaks <- which(diff(as.numeric(by(x, ...))) != 0)
breaks <- c(0, breaks, NROW(x))
return(breaks)
}
period.apply <-
function (x, INDEX, FUN, ...)
{
FUN <- match.fun(FUN)
y <- NULL
for (i in 1:(length(INDEX) - 1)) {
sindex <- (INDEX[i] + 1):INDEX[i + 1]
dat <- x[sindex]
y <- c(y, FUN(dat, ...))
}
return(y)
}
Jeff Ryan
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