问题
I am familiar with the zoo function rollapply which allows you to do rolling computations on zoo or xts objects and you can specify the rolling increment via the by parameter. I am specifically interested in applying a function every month but using all of the past daily data in the computation. For example say my data set looks like this:
dte, val
1/01/2001, 10
1/02/2001, 11
...
1/31/2001, 2
2/01/2001, 54
2/02/2001, 34
...
2/30/2001, 29
I would like to select the end of each month and apply a function that uses all the daily data. This doesn't seem like it would work with rollapply since the by argument would be 30 sometimes, 29 other months, etc. My current idea is:
f <- function(xts_obj) { coef(lm(a ~ b, data=as.data.frame(xts_obj)))[1] }
month_end <- endpoints(my_xts, on="months", k=1)
rslt <- apply(month_end, 1, function(idx) { my_xts[paste0("/",idx)] })
Surely there is a better way to do this that would be quicker no? To clarify: I would like to use overlapping periods just the rolling should be done monthly.
回答1:
If I understand correctly, you can get the dates of your endpoints, then for each endpoint (i.e. using lapply or for), call rollapply using data up to that point.
getSymbols("SPY", src='yahoo', from='2012-01-01', to='2012-08-01')
idx <- index(SPY)[endpoints(SPY, 'months')]
out <- lapply(idx, function(i) {
as.xts(rollapplyr(as.zoo(SPY[paste0("/", i)]), 5,
function(x) coef(lm(x[, 4] ~ x[, 1]))[2], by.column=FALSE))
})
sapply(out, NROW)
#[1] 16 36 58 78 100 121 142 143
I temporarily coerce to zoo for the rollapplyr to make sure the rollapply.zoo method is being used (as opposed to the unexported rollapply.xts method), then coerce back to xts
回答2:
As an answer to "Is the zoo/xts conversion needed?": It isn't needed in this case, but rollapply won't work if you send it a dataframe, as I recently discovered from this StackOverflow answer
回答3:
You want period.apply(), or its convenience helper apply.monthly(), both in xts.
Example:
R> foo <- xts(1:100, order.by=Sys.Date()+0:99)
R> apply.monthly(foo, sum)
[,1]
2012-08-31 105
2012-09-30 885
2012-10-31 1860
2012-11-25 2200
R>
or equally
R> apply.monthly(foo, quantile)
0% 25% 50% 75% 100%
2012-08-31 1 4.25 7.5 10.75 14
2012-09-30 15 22.25 29.5 36.75 44
2012-10-31 45 52.50 60.0 67.50 75
2012-11-25 76 82.00 88.0 94.00 100
R>
just to prove that functions returning more than one value can be used too.
来源:https://stackoverflow.com/questions/12021171/rolling-computations-in-xts-by-month