R help - Aug 2011 - aggregate.zoo on bivariate data

Hi,

I'm removing non-unique time indices in a zoo time series by means of
aggregate. The time series is bivariate, and the row to be kept only depends
on the maximum of one of the two columns. Here's an example:

x <- zoo(rbind( c(1,1), c(1.1, 0.9), c(1.1, 1.1), c(1,1) ),
        order.by=c(1,1,2,2))

The eventual aggregated result should be

1   1.1   0.9
2   1.1   1.1

that is, in each slice of the underlying data (a slice being all rows with
the same time stamp), we take the row that has maximum value in the first
column. (For the moment, let's not worry about several rows within the same
slice having the same maximum value in the first column.)

I have tried subsetting x by

slices <- aggregate(x[,1], by=identity, FUN=which.max)

but ended up with something as ugly as:

T <- length( unique(time(x)) )
result <- zoo( matrix(NA, ncol=2, nrow=T), order.by=unique(time(x)) )

for(t in seq(length.out=T))
{
    result[t,] <- x[ time(x)==time(slices[t]) ][coredata(slices[t]),]

}

There must be a better way of doing this -- maybe using tapply or the plyr
package, but possibly something much simpler. Any pointers are very welcome.
Thanks, Jo

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On Mon, Aug 8, 2011 at 9:16 AM, Johannes Egner <johannes.egner at
gmail.com> wrote:
> Hi,
>
> I'm removing non-unique time indices in a zoo time series by means of
> aggregate. The time series is bivariate, and the row to be kept only
depends
> on the maximum of one of the two columns. Here's an example:
>
> x <- zoo(rbind( c(1,1), c(1.1, 0.9), c(1.1, 1.1), c(1,1) ),
> ? ? ? ?order.by=c(1,1,2,2))
>
> The eventual aggregated result should be
>
> 1 ? 1.1 ? 0.9
> 2 ? 1.1 ? 1.1
>
> that is, in each slice of the underlying data (a slice being all rows with
> the same time stamp), we take the row that has maximum value in the first
> column. (For the moment, let's not worry about several rows within the
same
> slice having the same maximum value in the first column.)
>
> I have tried subsetting x by
>
> slices <- aggregate(x[,1], by=identity, FUN=which.max)
>
> but ended up with something as ugly as:
>
> T <- length( unique(time(x)) )
> result <- zoo( matrix(NA, ncol=2, nrow=T), order.by=unique(time(x)) )
>
> for(t in seq(length.out=T))
> {
> ? ?result[t,] <- x[ time(x)==time(slices[t]) ][coredata(slices[t]),]
>
> }
>
> There must be a better way of doing this -- maybe using tapply or the plyr
> package, but possibly something much simpler. Any pointers are very
welcome.
Where does the data come from in the first place?  Is it being read
in?  or is it in a data frame that is converted to a zoo object?

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