Hi:
1. I am working with the spacetime package and have successfully ingested a
dataset into its *irregular* space-time data frame using coordinates for
space, an xts object for time and auxiliary data for the attribute data.
Next I tried to create a sparse space-time data frame (i.e. a grid) using
the same pieces of data is successfully used before, plus the additional
index. The STSDF function choked on the xts data that I tried to provide it
with. The documentation on the sparse space-time data frame is, excuse the
pun, sparse. There is no indication that the data structure to represent
time is any different. The exact error message I get is:
Error in checkSlotAssignment(object, name, value) :
  c("assignment of an object of class \"POSIXct\" is not valid for slot
\"time\" in an object of class \"ST\"; is(value, \"xts\") is not TRUE",
"assignment of an object of class \"POSIXt\" is not valid for slot \"time\"
in an object of class \"ST\"; is(value, \"xts\") is not TRUE")

2.  Unrelated to this I have a more general question of understanding. After
creating and plotting the irregular space-time data frame, I tried to coerce
it into a full grid, alas without success. Section 7.2 of the vignette
illustrates how to move from a full grid to a sparse or irregular one and
then back again. Could it be that starting with an irregular one does not
work? I kind of would understand that because mere coercion does not provide
all the information needed - which is why I ended up trying to create the
gridded data frames directly (my first question).

3.  Finally, the data that I am trying to massage are buoy paths expressed
as a good 22 million individual space-time points. I was thinking of using
the irregular space-time data frame structure to create the 14,855 buoy
paths (all buoys send their location information every six hours, some buoys
survive for up to eight years) and then to interpolate ocean current
surfaces similar to the Irish wind example in the spacetime vignette. The
vignette example uses full grids; will I be able to do that with the sparse
space-time data frames because the full matrix of the full grid would
certainly go beyond the capabilities of 'R'?

Cheers,
     Jochen

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