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()
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)")