[R-sig-Geo] about ST kriging

[Pınar Aslantas Bostan]

Hi Edzer,

Thank you very much for your mail. I found two records have identical location, but it is not my fault because I checked the original source data and it is erroneous. 

Now I have another problem; R gives another error message:
Error: cannot allocate vector of size 95.4 Mb

My computer includes 32-bit Windows and  3,5 GB RAM. I am not sure if I install 64-bit Windows, then the problem is solved? Or maybe I should minimize the data. Do you have any idea about it?

Best wishes,
Pinar

-----Original Message-----
From: r-sig-geo-bounces at r-project.org [mailto:r-sig-geo-bounces at r-project.org] On Behalf Of Edzer Pebesma
Sent: Wednesday, September 21, 2011 3:46 PM
To: r-sig-geo at r-project.org
Subject: Re: [R-sig-Geo] about ST kriging

Hi Pinar,

it is not clear which variogram model you pass, or how your data are
laid out in space and time.

Possible causes for a non-positive definite covariance matrix include:

- a variogram model with (nearly) perfect correlation
- duplicate observations (observations having identical location AND time)
- an invalid variogram model

A small, reproducible example (data + script) would help identify the
problem.

Best regards,
--
Edzer

On 09/20/2011 11:15 AM, Pınar Aslantas Bostan wrote:
> Dear all,
> 
> I am working about space-time kriging. Before I asked again about ST kriging
> but now the problem is 
> different and I could not overcome it!
> 
> During kriging operation I got this error:
> 
>> pred = krigeST(prec~1, w, STS(grid,time,index), v)
> Error in chol.default(A$Sm, LINPACK = TRUE) : 
>   non-positive definite matrix in 'chol'
> 
> I explained the data set below:
> 
> # prec is annual precipitation measured from 257 meteorological stations
> 
> # w is STSDF object
>> summary(w)
> Object of class STSDF
> [[Spatial:]]
> Object of class SpatialPoints
> Coordinates:
>          min     max
> Xnew  140556 1730472
> Ynew 4309064 4971309
> Is projected: NA 
> proj4string : [NA]
> Number of points: 257
> [[Temporal:]]
>      Index                      object at time  
>  Min.   :1970-01-01 12:00:00   Min.   : 1.0  
>  1st Qu.:1979-07-03 00:00:00   1st Qu.:10.5  
>  Median :1989-01-01 12:00:00   Median :20.0  
>  Mean   :1989-01-01 02:46:09   Mean   :20.0  
>  3rd Qu.:1998-07-03 00:00:00   3rd Qu.:29.5  
>  Max.   :2008-01-01 12:00:00   Max.   :39.0  
> [[Data attributes:]]
>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
>   114.5   413.7   533.6   633.0   735.6  3332.0 
> 
> # I used grid to obtain predictions over it. It has 25 km spatial resolution
> 
> # time is temporal entity of study. It contains 39 annual observation.
> 
> # index is required for STSDF, and I used this code to create index.
>> index <- cbind(as.integer(as.factor(data$Station)),
> as.integer(as.factor(data$Year)))
> 
> # v is space-time variogram
> 
> How can I solve the problem?
> Thank you in advance!
> 
> 
> Pinar Aslantas Bostan
> Research Assistant
> Department of Geodetic and
> Geographic Information Technologies (GGIT) Middle East Technical University
> 06531 Ankara/TURKEY
> aslantas at metu.edu.tr
> 
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo

-- 
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster
Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251
8333081, Fax: +49 251 8339763  http://ifgi.uni-muenster.de
http://www.52north.org/geostatistics      e.pebesma at wwu.de

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