RE: AI-GEOSTATS: Non-Monotone Variogram model
Title: RE: AI-GEOSTATS: Non-Monotone Variogram model Dear Yadollah, have a look to see if you have any strong outliers using a variogram cloud. Your potential drift may simply be a single erroneous or extreme value, which once removed will cause your variogram to stabilise, Benjamin Warr Research Associate to Prof. Ayres, Geostatistician, Environmental Scientist. Postal Address: Centre for the Management of Environmental Resources (CMER) INSEAD Boulevard de Constance, 77305 Fontainebleau Cedex, France Tel: 33 (0)1 60 72 4456 Fax: 33 (0)1 60 74 55 64 e-mail: [EMAIL PROTECTED] > -Original Message- > From: Yadollah (Majid) Waghei [mailto:[EMAIL PROTECTED]] > Sent: Sunday, May 06, 2001 12:07 PM > To: [EMAIL PROTECTED] > Cc: [EMAIL PROTECTED]; [EMAIL PROTECTED] > Subject: AI-GEOSTATS: Non-Monotone Variogram model > > > Hello list members > My Empirical Variogram for a spatial data set has an cubic > like form(see below). Then the ordinary variogram models such > as Exponential, Gaussian, Linear, Spherical models is not > best fit to my data( Because these models are monotone > (increasing) functions). Then I need to a suitabe variogram > model for such Data. > > A graph of semivariogram > gamma(h) > | . > | . > | . . > | . . > | . . . > | . . . > | . .. > | . > | . > | . . . . > | . . . > |_ h > Thank you > Waghei > Dep.of Biostatistics > Tarbiat Modarres Univ.(Tehran)Po.Box: 14115-111 > Tel:8011001-3872 Fax:8007989 > __ > _ > Visit http://www.visto.com/info, your free web-based > communications center. > Visto.com. Life on the Dot. > > > -- > * 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: Non-Monotone Variogram model
> A graph of semivariogram > gamma(h) > |. > | . > | . . > |.. > | .. . > |. . . > | . .. > | . > | . > |. . . . > | . . . > |_ h ^ Waghei If this is an omni-directional semi-variogram, then what you have is a severe case of anisotropy probably complicated by a strong trend. I would hazard a guess that you start to runout of pairs of samples in one or more directions somewhere around the ^ above. Try constructing directional semi-variograms and post-plotting the data to identify directional differences. Isobel Clark http://uk.geocities.com/drisobelclark Do You Yahoo!? Get your free @yahoo.co.uk address at http://mail.yahoo.co.uk or your free @yahoo.ie address at http://mail.yahoo.ie -- * 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: Non-Monotone Variogram model
Dear Waghei, At first I would not trust only in the traditional semivariogram. You should better use more robust measures to evaluate the semivariogram structures. There are several possibilities like correlogram or other standardized variogram estimators (Srivastava, Parker 1989 - see below for full reference). They are robust against outliers/extreme values, positive skewness. Did you test for a trend? In addition, did you try to vary the lag distance? Perhaps you will get a better spatial continuity if you increase/decrease it. If there should be a periodic structure you could use for variogram modelling the periodical or hole effect model. But first you should think of the underlying physical processes. Hope this helps, Ulrich References: Srivastava, R.M.; Parker, H.M. 1989: Robust measures of spatial continuity. In: Armstrong, M.1989 (Ed.): Geostatistics. Vol.1, Dordrecht, p. 295-308. On 2001.05.06 12:07:01 +0200 Yadollah (Majid) Waghei wrote: > Hello list members > My Empirical Variogram for a spatial data set has an cubic like form(see > below). Then the ordinary variogram models such as Exponential, > Gaussian, Linear, Spherical models is not best fit to my data( Because > these models are monotone (increasing) functions). Then I need to a > suitabe variogram model for such Data. > > A graph of semivariogram > gamma(h) > |. > | . > | . . > |.. > | .. . > |. . . > | . .. > | . > | . > |. . . . > | . . . > |_ h > Thank you > Waghei > Dep.of Biostatistics > Tarbiat Modarres Univ.(Tehran)Po.Box: 14115-111 > Tel:8011001-3872 Fax:8007989 > ___ > Visit http://www.visto.com/info, your free web-based communications > center. > Visto.com. Life on the Dot. > > > -- > * 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 > > -- Ulrich Leopold MSc. Engelstrasse 104 D-54292 Trier Germany Phone: +49-(0)651-140764 E-mail: [EMAIL PROTECTED] URL: http://www.geocities.com/leop6101/index.htm -- * 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: Non-Monotone Variogram model
Hello list members My Empirical Variogram for a spatial data set has an cubic like form(see below). Then the ordinary variogram models such as Exponential, Gaussian, Linear, Spherical models is not best fit to my data( Because these models are monotone (increasing) functions). Then I need to a suitabe variogram model for such Data. A graph of semivariogram gamma(h) |. | . | . . |.. | .. . |. . . | . .. | . | . |. . . . | . . . |_ h Thank you Waghei Dep.of Biostatistics Tarbiat Modarres Univ.(Tehran)Po.Box: 14115-111 Tel:8011001-3872 Fax:8007989 ___ Visit http://www.visto.com/info, your free web-based communications center. Visto.com. Life on the Dot. -- * 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
