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 -- View this message in context: http://r-sig-geo.2731867.n2.nabble.com/What-is-the-reason-for-Very-high-value-by-Universal-Kriging-based-on-Nested-3D-varigram-tp7587514.html Sent from the R-sig-geo mailing list archive at Nabble.com.
What is the reason for Very high value by Universal Kriging based on Nested 3D varigram
3 messages · Bingwei Tian, Edzer Pebesma, Jon Olav Skoien
You don't describe your problem completely, and you also do not provide a reproducible example, so I can only make a wild guess: your z variable takes an extreme value at the prediction location(s) where you see the high predictions.
On 12/04/2014 08:19 AM, Bingwei Tian wrote:
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 -- View this message in context: http://r-sig-geo.2731867.n2.nabble.com/What-is-the-reason-for-Very-high-value-by-Universal-Kriging-based-on-Nested-3D-varigram-tp7587514.html Sent from the R-sig-geo mailing list archive at Nabble.com.
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Edzer Pebesma, Co-Editor-in-Chief Computers & Geosciences Institute for Geoinformatics (ifgi), University of M?nster Heisenbergstra?e 2, 48149 M?nster, Germany. Phone: +49 251 83 33081 http://ifgi.uni-muenster.de GPG key ID 0xAC227795 -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 490 bytes Desc: OpenPGP digital signature URL: <https://stat.ethz.ch/pipermail/r-sig-geo/attachments/20141204/1e970c8e/attachment.bin>
It is difficult for us to know exactly what happens as you are not providing a reproducible example. But my guess would be that this is related to your use of a Gaussian variogram without nugget for the first part of the variogram. This can cause rather large weights (positive and negative) if you have observations in close vicinity of each other, leading to predictions far away from your range of observations. See if a small nugget effect (~0.01 or less) can solve the problem, or if you can change to a different variogram model. Cheers, Jon
On 12/4/2014 8:19 AM, Bingwei Tian wrote:
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 -- View this message in context: http://r-sig-geo.2731867.n2.nabble.com/What-is-the-reason-for-Very-high-value-by-Universal-Kriging-based-on-Nested-3D-varigram-tp7587514.html Sent from the R-sig-geo mailing list archive at Nabble.com.
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Jon Olav Sk?ien Joint Research Centre - European Commission Institute for Environment and Sustainability (IES) Climate Risk Management Unit Via Fermi 2749, TP 100-01, I-21027 Ispra (VA), ITALY Disclaimer: Views expressed in this email are those of the individual and do not necessarily represent official views of the European Commission.