[R-sig-Geo] How does variogramST handle NAs?

[Edzer Pebesma]

Dear Nick, did you use the r-forge binaries? This was suggested in

https://stat.ethz.ch/pipermail/r-sig-geo/2013-January/017234.html

Please let me know if your unexpected results persist, and also tell us 
what was unexpected.



On 02/03/2013 01:40 PM, Nick Hamm wrote:
> Dear list
>
> We have been working with an STFDF object.  The dataset contains
> several NAs, that is to say that there are some locations where the
> time-series record is incomplete.  When we computed space-time
> variograms for this dataset we found some unexpected results.
>
> To explore this further, we took a second dataset of measurements from
> the same location.  This dataset is complete (i.e., there are no NAs).
>   We computed the space-time variogram.  We then inserted NAs at the
> location that they occur for the first dataset and get quite different
> variograms!
>
> My question is:  How does variogramST handle NAs?
>
> Demo code is below.  You can download the data from here:
>
> https://dl.dropbox.com/u/15122401/demoData.zip
>
> Nick
>
>
> sessionInfo()
>
>> sessionInfo()
> R version 2.15.2 (2012-10-26)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
>
> locale:
> [1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United
> Kingdom.1252
> [3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C
> [5] LC_TIME=English_United Kingdom.1252
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] gstat_1.0-15    spacetime_1.0-3 sp_1.0-5
>
> loaded via a namespace (and not attached):
> [1] grid_2.15.2      intervals_0.13.3 lattice_0.20-10  tools_2.15.2
> [5] xts_0.9-3        zoo_1.7-9
>>
>
>
> # Load required libraries
> require(gstat)
> require(spacetime)
>
> # Load the demo data
> rm(list=ls())
> load("demoData.RData")
>
> # jan.na has some NAs in time
> summary(jan.na$value)
> # LE is at the same location but has no NAs
> summary(LE$value)
>
> # ST variogram for LE - full dataset
> v.all <- variogramST(value~1, LE, width=20000, cutoff=500000,tlags=0:6)
> plot(v.all, ylab="time lag (days)", xlab="distance (km)")
> plot(v.all, map=FALSE, ylab="time lag (days)", xlab="distance (km)")
>
>
> # Now insert NA's into the full dataset. The NA's correspond to  those
> in the "jan.na" dataset
> loc.na <- which(jan.na$value > 0)
> LE.na  <- LE
> LE.na$value[-loc.na] <- NA
>
> # ST variogram - dataset with NA's inserted
> v.na <- variogramST(value~1, LE.na, width=20000, cutoff=500000,tlags=0:6)
> plot(v.na, ylab="time lag (days)", xlab="distance (km)")
> plot(v.na, map=FALSE, ylab="time lag (days)", xlab="distance (km)")
>
>
>
> # Remove all locations where there are any NAs in the jan.na time series
> any.na <- which(apply(as(jan.na, "xts"), 2, function(x) all(!is.na(x))))
> LE.no=LE[any.na,]
>
> # ST variogram - remove all locations where there is an NA
> v.any <- variogramST(value~1, LE.no, width=20000, cutoff=500000,tlags=0:6)
> plot(v.any, ylab="time lag (days)", xlab="distance (km)")
> plot(v.any, map=FALSE, ylab="time lag (days)", xlab="distance (km)")
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>