[R] how apply.monthly() in package xts works

[Joshua Ulrich]

On Thu, Mar 9, 2017 at 3:31 PM, Waichler, Scott R
<Scott.Waichler at pnnl.gov> wrote:
> Hi,
>
> I found that apply.monthly() in xts does not work as I expected in the case of a sparse timeseries:
>
> my.dates <- as.Date(c("1992-06-01", "1992-06-24", "1992-06-30", "1993-06-22", "1994-06-07", "1995-06-08"))
> my.xts <- xts(1:6, my.dates)
> start(my.xts)  # "1992-06-24"
> end(my.xts)  # "1995-06-08"
> apply.monthly(my.xts, mean)
> #           [,1]
> # 1995-06-08 3.5
>
> The endpoints it chooses are based on looking at the month (June) alone.  I was able to get a value for each (month, year) in the timeseries with the following use of aggregate():
>
Thanks for the minimal, reproducible example!  This is clearly a bug.

> my.months <- months(my.dates)
> my.years <- years(my.dates)
> df1 <- data.frame(x = coredata(my.xts), dates = my.dates, months = my.months, years = my.years)
> df2 <- aggregate(df1[-c(3,4)], df1[c("months", "years")], mean)
> xts(df2$x, df2$dates)
> #            [,1]
> # 1992-06-18    2
> # 1993-06-22    4
> # 1994-06-07    5
> # 1995-06-08    6
>
> Two questions:
> 1) Is there a more elegant way to do this?

Create your own endpoints until endpoints() is fixed.  Here's a quick
hack, off the top of my head:

endpointsMonthHack <- function(x, on = "months", k = 1) {
  # yearmon index
  ymIndex <- as.yearmon(index(x))
  # month changes
  monthDiff <- c(0, diff(ymIndex))
  # locations in index
  locations <- which(monthDiff != 0)
  ep <- c(0, locations, nrow(x))
  unique(ep)
}

> 2) Shouldn't the xts documentation discuss the problem of sparse data?

No, because it shouldn't be a problem. :)

>
> Regards,
> Scott Waichler
> Pacific Northwest National Laboratory
> Richland, WA  USA
>
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