[R] aggregation of irregular interval time-series

[Bert Gunter]

I have *not* followed this in any detail, but this line seems wrong:

arvaia_catture_order <- arvaia_catture[order(arvaia_catture$tempo)]

Perhaps it should be:
arvaia_catture_order <- arvaia_catture[order(arvaia_catture$tempo), ] ##
note the comma!

If I am mistaken, just ignore and move on.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Wed, Jun 9, 2021 at 2:41 PM Rui Barradas <ruipbarradas using sapo.pt> wrote:

> Hello,
>
> I'm not getting your simple sum:
>
>
> arvaia_catture_order[, week := as.integer(format(tempo, "%U"))]
> aggregate(catture ~ week, arvaia_catture_order, sum)
> #  week catture
> #1   19      15
> #2   20       5
> #3   21      78
> #4   22     120
>
>
> Can you explain your result better?
>
> Hope this helps,
>
> Rui Barradas
>
> Às 18:57 de 09/06/21, Enrico Gabrielli escreveu:
> > Hello
> > I just registered on the list.
> > I am an agricultural technician and I am collaborating on a research
> > project on agroforestry and Brown Marmorated Stink Bug (Halyomorpha
> > halys, abbreviated BMSB).
> >
> > Through kobotoolbox we are collecting data of catches in traps on
> > farms. Farms register inconsistently.
> > I am trying to use packages for irregular time series.
> >
> > Here an exemple
> > the data:
> > # variable monitoring time as register an import from kobotoolbox
> > tempo <- as.POSIXct(c("2021-05-29 17:00:00 UTC","2021-06-05 10:52:00
> > UTC","2021-06-01 17:00:00 UTC","2021-05-16 08:34:00 UTC","2021-06-05
> > 17:00:00 UTC","2021-05-29 05:30:00 UTC","2021-05-23 06:30:00
> > UTC","2021-05-20 13:00:00 UTC","2021-05-15 12:09:00 UTC"))
> > # variable capture of BMSB
> > catture <- c(25,92,23,2,5,30,23,3,15)
> > # resulting table
> > library(data.table)
> > arvaia_catture <- data.table(tempo,catture)
> > # order by time
> > arvaia_catture_order <- arvaia_catture[order(arvaia_catture$tempo)]
> >
> > the catches refer to an interval, which goes from the previous
> > monitoring up to the one recorded on the date
> > our aim is to calculate the weekly catch
> > also when a farmer, for example, enters the data on Thursday and
> > Tuesday
> > of the following week, on Tuesday in the trap he will find individuals
> > who were also captured on Friday and Saturday, which formally are to be
> > considered in the previous week.
> >
> > With the data of the example
> > the results (with a spreadsheet) is
> > two possibile solution
> > week            simple SUM week         right SUM week
> > 19      17      19,44027778
> > 20      26      52,91388889
> > 21      55      46,4375integrand_2 <- function(x) {0.62 * (1/x)}
>
> integrate(integrand, lower = , upper = 5)
>
> > 22      120     99,20833333
> > The right SUM week is right!
> >
> > I have made several attempts
> > with lubridate, padr, xts
> > but the last one seems interesting to me
> > with DTSg
> > doing
> > x_periodic <- alter(x,na.status = 'explicit',from="2021-05-15
> > 12:00:00",by="min")
> > colapply(x_periodic, fun = interpolateLinear)
> > I managed to create a vector with all interpolated hours
> > but with DTSg I still can't aggregate by week
> >
> > Has anyone on the list ever faced such a problem?
> >
> > Thank you
> >
>
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