Is it possible to get the specific index of occurence when working with period.apply?

Assuming I worked with meteorological observations and wanted to know not only the daily maximum value but also the relevant timestamp, describing when this value was observed, is it possible to accomplish this without significant overhead, e.g. by setting some sort of parameter?

library(xts)set.seed(42)# init datadatetimes <- seq(from = as.POSIXct("2022-01-01"),                  to = as.POSIXct("2022-01-08"),                 by = "10 mins")values <- length(datetimes) |> runif() |> sin()data <- xts(x = values,            order.by = datetimes)# ep <- endpoints(data, "days")data_max <- period.apply(data, INDEX = ep, FUN = max)head(data_max)#>                          [,1]#> 2022-01-01 23:50:00 0.8354174#> 2022-01-02 23:50:00 0.8396034#> 2022-01-03 23:50:00 0.8364624#> 2022-01-04 23:50:00 0.8376930#> 2022-01-05 23:50:00 0.8392988#> 2022-01-06 23:50:00 0.8372780

Obviously, this would work well with summarizing functions like mean and median where you would want to specify the interval width considered, but when working with e.g. min and max, how would I proceed when I wanted to know the exact index of the value in question observed.

At the moment, I'm just looping over my xts subsets to determine the relevant index, but maybe there is a more elegant approach, maybe even an argument when using period.apply() I haven't noticed to get this information.

sub <- "2022-01-04"ind <- which(data[sub] == max(data[sub]))data[sub][ind]#>                         [,1]#> 2022-01-04 23:20:00 0.837693

My desired output would look like this:

#>                          [,1]#> 2022-01-01 03:40:00 0.8354174#> 2022-01-02 15:00:00 0.8396034#> 2022-01-03 05:10:00 0.8364624#> 2022-01-04 23:20:00 0.8376930#> 2022-01-05 02:50:00 0.8392988#> 2022-01-06 06:40:00 0.8372780