Re: [AI-GEOSTATS: Deterministic vs. Stochastic Interpolation Comparison]
Hi Gregoir, Hi Mailinglist ! thank you very much for the information ! I am analysing plants in grassland and I have the problem, that many researchers here use linear triangulation in r e g u l a r (20 x 20 metres) sampling grids to estimate the population for mapping. Natural Neighbors seems to be very similar. My question now would be what does surfer do, when the edge parts of a grsslandfield are cross-validated (as you already mentioned there is NO extrapolation) This should result in larger RMSE errors compared to any other extrapolation method !?? I am not shure if I can use these cross-validation results to compare the efficiacy or performance of a interpoolation method in that particular case and in general. (By the way: Do you think it is correct to use the best cross-validation results of a interoplation method to compre its performance to another method? Is a jackknifing nessecary in addition) Another question I would like to ask you is whether you think that if I would have the spatial location of every single plant in an area; Could I start comparing sampling schemes and interpolators much better ? Which way to do so would you choose ? I hope you can help me with some of your amazing answers, Peter From: Gregoire Dubois <[EMAIL PROTECTED]> To: "Peter Pinn" <[EMAIL PROTECTED]>, <[EMAIL PROTECTED]> Subject: Re: [AI-GEOSTATS: Deterministic vs. Stochastic Interpolation Comparison] Date: Tue, 02 Sep 2003 16:23:25 +0200 Peter, the RMSE is not THE measure of cross-validation... it is only one of the possible statistics of the errors you can use. Fundamentaly, what you get from cross-validations is a set of estimated values that can be compared to the input data. Hence, you can use various statistics of the errors (error = observed - estimated value): the RMSE, the MAE (mean absolute error), the correlation coefficient between observed values and estimates... you can also focus on the highest values only. You have to define the criteria that will quantify the "performance" of the interpolators before doing any cross-validation. The RMSE is probably the measure that is the most frequently used. Surfer's (version 8 only) cross-validation function seems to work fine now (see my posting in the archives about the bug I found a few months ago). You have to update your original version to 8.2. As you mention, a few deterministic interpolators do not allow extrapolations (estimations outside the boundary defined by the convex hull), but many do (IDW, polynomes,...). I don't know what kind of variables you are analysing, but geometrical interpolators (triangulations, thiessen polygons, nearest neighbours) are almost never used for estimation purposes in environmental sciences, unless you have very large data sets. Gregoire "Peter Pinn" <[EMAIL PROTECTED]> wrote: > Hello, > > thank you all for the great replies to my questions. This helps very much. > > I was wondering whether or not there is a way to compare the performance of > deterministic interpolation methods such as Linear Triangulation or Natural > Neighbours to Kriging or IDW !? Is there a measure similar to the RMSE > resulting from cross-validation ? (e.g. ESRIs Geostatistical Analyst does > not use these methods, whereas SURFER applies a cross-validation that I do > not really believe in !) I hope I am not totally wrong assuming that > cross-validation does not really work fine in deterministic methods, because > a extrapolation at edge sampling locations will not be computed... > > Thanks again :-) > > Peter > > _ > Add photos to your e-mail with MSN 8. Get 2 months FREE*. > http://join.msn.com/?page=features/featuredemail > > > -- > * To post a message to the list, send it to [EMAIL PROTECTED] > * As a general service to the users, please remember to post a summary of any useful responses to your questions. > * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list > * Support to the list is provided at http://www.ai-geostats.org > _ STOP MORE SPAM with the new MSN 8 and get 2 months FREE* http://join.msn.com/?page=features/junkmail -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: Lag - Distance, Variogram / Semivariogram
Hi there, can anybody here tell me how to choose the correct (appropriate) lag distance for a regular sampling grid for orchids of 5.5 x 20 metres (Counting data at a certain quadrate) ? I have problems in variogrphy, because lag distances of 5 metres seem to be problematic because of the regularity of the sampling grid and the missing values inbetween the 20 meteres distances. If I choose a 15 metres lag I get a much smoother variogram. Choosing a 5 metres lag, the variance values are too high in the frist 3 -4 lags. My second question is what is the difference between a variogram and a semivariogram ? Is there any ? Is a correlogram easier to interprete ? I found it much easier to deal with values of my diagram between 0 and 1 rather than having trouble to interprete a particular variance x !!?? Hopefully you can help a newbie. Ursula:-) _ MSN Groups & Chat - Freunde finden - leicht gemacht http://groups.msn.com/people/ -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: negative weight
Hi Mailinglist!!! I have got some problems with negative weight in my cokriging, they induce negative grade. Have you got some advice or publication to help me.I hope you can help me with some of your answers. Thank Laure Laure FONTAINE Services des Réserves COGEMA BUM/DT tél: 33 1 39 26 32 05 Fax: 33 1 39 26 27 31 -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS:
Laure FONTAINE Services des Réserves COGEMA BUM/DT tél: 33 1 39 26 32 05 Fax: 33 1 39 26 27 31 -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: Lag - Distance, Variogram / Semivariogram
Ursula > 5.5 x 20 metres > Choosing a 5 metres lag, the variance > values are too high in the first 3 -4 lags. This is possibly because you have some competition effect between orchids. For a square grid, we usually recommend an interval 20% of the grid spacing, so you don't get diagonals lumped in with 'straight' directions. This would suggest that you should try a 1 metre lag, which is probably overkill. The other alternative is to construct directional semi-variograms and specify the correct lag for each direction, to see what differences you get. > My second question is what is the difference between > a variogram and a semivariogram ? As a general rule a "variogram" is a semi-variogram constructed by someone lax in their terminology. No software I know calculates the true variogram (twice the semi-variogram). The correlogram is simply the semi-variogram upside down and standardised to vary between -1 and +1. The disadvantage of this approach (or the covariance function is that it is difficult to assess the nugget effect accurately. You should be concerned about your variance as it provides essential information about teh variability of your phenomenon. Isobel Clark http://ecosse.ontheweb.com/whatsnew.htm Want to chat instantly with your online friends? Get the FREE Yahoo! Messenger http://mail.messenger.yahoo.co.uk -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: negative weight
Laure You will probably get lots of replies on this and plenty of references, so I will stick to what I know. Possible reasons for large negative weights: (a) samples are too close together with low nugget effects on the semi-variogram models. This leads to precision problems in solving the equations for the kriging and gives unstable results (b) the nugget effect on your cross semi-variogram is too low, same problem as (a) (c) your negative weights are not so large but your data is (for example) highly skewed. In this case you may get a fairly small negative weight on a very large sample value. Your problem here is not negative weights but the skewness on your data. Hope this helps Isobel http://uk.geocities.com/drisobelclark Want to chat instantly with your online friends? Get the FREE Yahoo! Messenger http://mail.messenger.yahoo.co.uk -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: negative weight
Hi Laure, One of the main culprits for negative cokriging weights is the ordinary cokriging constraint that the sum of the secondary weights must be zero. I found that the frequency and magnitude of negative cokriging weights greatly decreased when using a single constraint that primary and secondary data weights must sum to one (referred to as standardized cokriging in Gslib software). This issue is discussed in my book and in the following publication: Goovaerts, P. 1998. Ordinary cokriging revisited. Mathematical Geology, 30(1): 21-42. Cheers, Pierre <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> Dr. Pierre Goovaerts President of PGeostat, LLC Chief Scientist with Biomedware Inc. 710 Ridgemont Lane Ann Arbor, Michigan, 48103-1535, U.S.A. E-mail: [EMAIL PROTECTED] Phone: (734) 668-9900 Fax: (734) 668-7788 http://alumni.engin.umich.edu/~goovaert/ <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> On Thu, 4 Sep 2003 [EMAIL PROTECTED] wrote: > Hi Mailinglist!!! > > I have got some problems with negative weight in my cokriging, they induce > negative grade. Have you got some advice or publication to help me.I hope > you can help me with some of your answers. > > Thank > > Laure > > > > Laure FONTAINE > Services des Réserves > COGEMA BUM/DT > tél: 33 1 39 26 32 05 > Fax: 33 1 39 26 27 31 > > > > -- > * To post a message to the list, send it to [EMAIL PROTECTED] > * As a general service to the users, please remember to post a summary of any useful > responses to your questions. > * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and > "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO > NOT SEND Subscribe/Unsubscribe requests to the list > * Support to the list is provided at http://www.ai-geostats.org > > -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: negative weight
Hi! There is something about negative weights in "geostatistics for natural Resources Evaluation" of Pierre Goovaerts. Also in Srivastava's "Applied geostatistics" you can find something of useful. Sebastiano At 05:29 PM 9/4/2003 +0200, [EMAIL PROTECTED] wrote: Hi Mailinglist!!! I have got some problems with negative weight in my cokriging, they induce negative grade. Have you got some advice or publication to help me.I hope you can help me with some of your answers. Thank Laure Laure FONTAINE Services des Réserves COGEMA BUM/DT tél: 33 1 39 26 32 05 Fax: 33 1 39 26 27 31 -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: gstat and anisotropy parameters.
Hi I have a set of two dimensional data( measured on a grid). Initial analysis strongly suggests that there is directional anisotropy, so I've been trying to deal with this. One way I've found is to fit the variogram model by maximum likelihood (or REML) using geoR. geoR seems to account for anisotropy by deforming the locations, according to the anisotropy parameters (direction of maximum range, and the anisotropy ratio). Cross--validation suggests that this performs well, relative to fitting various models to isotropic sample variogram. The thing is, I want to use gstat for kriging. The reason for this is that I want to do block kriging. However, gstat seems to account for anisotropy by adjusting the variogram range according to the anisotropy parameters. So it seems that geoR deforms the coordinates, whereas gstat "deforms" the variogram The upshot of this is that, when I use gstat to do punctual kriging using the parameters estimated in geoR, I get different results to what I get when I use geoR for kriging. A possible alternative, is to use geoR to predict the deformed locations, and then use gstat to do the kriging WITHOUT specifying the anisotropy parameter. If I do this then gstat and geoR give the same results for kriging. This suggests that there is no difference in the algorithms used for kriging between the two packages. This approach seems to be OK for doing punctual kriging... However, I want to do block kriging (square blocks). The approach I've adopted for punctual kriging seems to fall over here. This is because I would specify the block size (in gstat) in the deformed coordinate space, whereas I actually want the blocks to be specified in the original geographic coordinate space. Am I making sense? What a mess!!! Can any one suggest an alternative, or is this all a bit silly? cheers Nick -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
