[R-sig-Geo] 'LDLfactor' error in 'krige' function

[Paul Hiemstra]

Edzer Pebesma wrote:
> My guess is that from constant data, the (co)variance is constant and
> zero, so the covariance matrix cannot be decomposed (hence: LDLfactor
> errors).
>
> Is this a case that autokrige should catch?
>   
I added a check in autoKrige. The output for the example below is now:

kriging_result = autoKrige(zinc~1, meuse)
Error in autoKrige(zinc ~ 1, meuse) :
  All data in attribute 'zinc' is identical and equal to 0
   Can not interpolate this data

A new version of automap with this feature has been uploaded to CRAN.

cheers,
Paul
> --
> Edzer
>
> Mauricio Zambrano wrote:
>   
>> Dear List,
>>
>> During some OK interpolations of daily precipitation, with the
>> 'automap' library, I got the following error:
>>
>>
>> [using ordinary kriging]
>> "chfactor.c", line 130: singular matrix in function LDLfactor()
>> Error en predict.gstat(g, newdata = newdata, block = block, nsim = nsim,  :
>>   LDLfactor
>>
>>
>> The code I'm using works fine for other days, so I assume that the
>> distance between the measurement points is no the problem. When
>> looking at the data that rose the error, I realized that all the
>> measured values were equal to zero (I can not skip those days in which
>> all the measured points have the same value in advance, because the
>> measured value in those points change with time).
>>
>> According to a traceback that is given below, it seems that the cause
>> is in the 'predict.gstat' function of the 'gstat' package.
>>
>> The same error can be risen with:
>>
>> # Data preparation
>> data(meuse)
>> coordinates(meuse) =~ x+y
>> data(meuse.grid)
>> gridded(meuse.grid) =~ x+y
>>
>> meuse$zinc <- meuse$zinc*0
>> meuse$zinc
>>
>> # Ordinary kriging, no new_data object
>> kriging_result = autoKrige(zinc~1, meuse)
>>
>>
>> traceback()
>> 6: .Call("gstat_predict", as.integer(nrow(as.matrix(new.X))),
>> as.double(as.vector(raw$locations)),
>>        as.vector(new.X), as.integer(block.cols), as.vector(block),
>>        as.vector(bl_weights), as.integer(nsim), as.integer(BLUE))
>> 5: predict.gstat(g, newdata = newdata, block = block, nsim = nsim,
>>        indicators = indicators, na.action = na.action, debug.level =
>> debug.level)
>> 4: .local(formula, locations, ...)
>> 3: krige(formula, input_data, new_data, variogram_object$var_model,
>>        block = block, ...)
>> 2: krige(formula, input_data, new_data, variogram_object$var_model,
>>        block = block, ...)
>> 1: autoKrige(zinc ~ 1, meuse)
>>
>>
>> I would really appreciate any hint about the possible reason of this
>> error and if it could be overcome in some way.
>>
>>
>> Thanks in advance for any help.
>>
>>
>> Mauricio
>>   
>>     
>
>   


-- 
Drs. Paul Hiemstra
Department of Physical Geography
Faculty of Geosciences
University of Utrecht
Heidelberglaan 2
P.O. Box 80.115
3508 TC Utrecht
Phone:  +3130 274 3113 Mon-Tue
Phone:  +3130 253 5773 Wed-Fri
http://intamap.geo.uu.nl/~paul