[R-sig-Geo] What is the reason for Very high value by Universal Kriging based on Nested 3D varigram

[Bingwei Tian]

Dear list,

I am doing a 3D estimation of logtransfered subsurface temperature (with a
strong vertical trend) with a Nested 3D variogram, but the results show very
high value over than origin data.
This is not normal and absolutely wrong if I back transfer logged data.

I attached the 
<http://r-sig-geo.2731867.n2.nabble.com/file/n7587514/vgm.png>  and anyone
who knows what is the reason for the very high value differ from origin
data?
Or what kind of processing I should to do for the data back transfer? Thanks
in advance for any help.

Data:
summary((spdf$logt))
          Min.        1st Qu.         Median           Mean        3rd Qu. 
0.741937344729 3.487375077900 3.908014984030 3.952886346280 4.452019006490 
          Max. 
5.733988316710 

Model: Nested 3D varigram
uk.eye1  <- vgm(psill = 0.155,  model = "Gau",  range=700,  nugget=0)
uk.eye   <- vgm(psill = 0.125,  model = "Sph",  range=35000,  nugget=0, 
add.to=uk.eye1)
  model psill range
1   Nug 0.000     0
2   Gau 0.155   700
3   Nug 0.000     0
4   Sph 0.125 35000
UK: 
logt.uk <- krige(log(t)~z, spdf, grid, model = uk.eye, nmax = 20)

Result:

summary((logt.uk$var1.pred))
          Min.        1st Qu.         Median           Mean        3rd Qu. 
-1.66562650678  3.30346488250  3.76836777085  3.81376070431  4.24457939254 
          Max. 
15.05945622140 



-----
Bingwei

Ph.D. Student 
Kyoto University
C-1-2-225, Katsura Campus, Kyoto University, 
Nishikyo-ku, 〒615-8530, Kyoto, Japan
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