Dear Perry Collier I`m interested in the second question: what is the difference between a dataset with a trend and a non-stationary dataset? Without clearly pointing out about which kind of stationarity we are talking (second order, intrinsic or generalized intrinsic), we need stationarity (well !!! togheter with ergodicity) for some statistical index (in this case a index about spatial variability) to perform inference. From my perspective the dualism trend-residual makes possible always (or not?) to explain non stationarity in spatial variability in term of presence of a trend: this trend could be global as well as local: it is only a matter of scale.The point is: we have reasons or so many data to use a complex trend model?
In particular this question makes me to think to a point. Very often people who use Universal Kriging do this: 1) detrend data globally (same trend coefficients for all spatial domain) 2) calculate a residual variogram 3) perfom Uk with local search windows (inside which the trend coefficients are calculated i.e. the trend is filtered locally) This doesen`t seem to me correct: I think (maybe, if you have many data IRF-K approach works better) that you can not one time calculate trend globally and the other time locally: it could happen that globally you need a quadratic trend while locally a linear trend model is enough. What about that? Sincerely, Sebastiano Trevisani At 03.48 07/07/2005, [EMAIL PROTECTED] wrote: Hi all I may know this already, but what are the symptoms of data with a trend? What is the difference between a dataset with a trend and a non-stationary dataset? Cheers Perry Collier Senior Mine Geologist Ernest Henry Mine Xstrata Copper Australia Ph (07) 4769 4527 Fx (07) 4769 4555 E-mail [EMAIL PROTECTED] Web http://www.xstrata.com PO Box 527 Cloncurry QLD 4824 Australia "Light travels faster than sound. That is why some people appear bright until you hear them speak" -----Original Message----- From: Pierre Goovaerts [mailto:[EMAIL PROTECTED] Sent: Friday, 1 July 2005 12:54 AM To: Recep kantarci; ai-geostats@unil.ch Subject: RE: [ai-geostats] modelling trend and kriging type To add to the excellent comments by Edzer and Gregoire, 1. Universal kriging = kriging with a trend. The second terminology has been proposed by Andre Journel who felt that the term "universal" was vague and misleadingly "ambitious". 2. Kriging with an external drift (KED) is mathematically the same as universal kriging (UK). Secondary variables are simply replacing the spatial coordinates used in UK. 3. Regression kriging denotes all the techniques where the trend is modeled outside the kriging algorithm. There are various methods that can be used to model that trend, ranging from linear regression to neural networks. Kriging is used to interpolate the residuals. In practice these techniques have more flexibility than universal kriging in term of modeling the trend: multiple variables either categorical or continuous can be incorporated easily and many sofwtare are available for this trend modeling. The only limitation is that the trend is modeled globally (i.e. the regression coefficients are constant in space) while in KED the coefficients are reestimated within each search window. Cheers, Pierre Pierre Goovaerts Chief Scientist at Biomedware 516 North State Street Ann Arbor, MI 48104 Voice: (734) 913-1098 Fax: (734) 913-2201 http://home.comcast.net/~goovaerts/ -----Original Message----- From: Recep kantarci [mailto:[EMAIL PROTECTED] Sent: Thu 6/30/2005 9:38 AM To: ai-geostats@unil.ch Cc: Subject: [ai-geostats] modelling trend and kriging type Dear ai-geostats members When the data used has a trend, it is needed to model trend and in this case there exists various types of kriging to apply (universal kriging, kriging with a trend, regression kriging etc). If this is the case, does one should use the same type of kriging or different depending on modeling the trend using coordinates of target variable or using other (namely, secondary or auxillary) variables such as elevation or topography ? That is , are there a dinstinction depending on the type of variables to model the trend while kriging? Best regards Recep _____ Yahoo! kullaniyor musunuz? Istenmeyen postadan biktiniz mi? Istenmeyen postadan en iyi korunma Yahoo! Postaâda http://tr.mail.yahoo.com <http://tr.mail.yahoo.com/> ********************************************************************** The information contained in this e-mail is confidential and is intended only for the use of the addressee(s). If you receive this e-mail in error, any use, distribution or copying of this e-mail is not permitted. You are requested to forward unwanted e-mail and address any problems to the Xstrata Queensland Support Centre. Support Centre e-mail: [EMAIL PROTECTED] Support Centre phone: Australia 1800 500 646 International +61 2 9034 3710 ********************************************************************** * By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm ) * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats ------------------------------------------------- This mail sent through IMP: webmail.unipd.it
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