AI-GEOSTATS: Choosing Lag Distance and Angular Tolerance
Hello dears I have a spatial data set contaning n=262 observarion (The variable of interest is Rate of Tuberculosis in 262 counties of Iran). I want to fit some models to Directional semi-variograms,and then build anisotropic semi-variogram. Then questions are - Is there any rule for choosing Lag Distance and Angular Tolerance? -Also,how we can balance between Lag Distance and Angular Tolerance? -Do you agree that both must be very small,as possible?(Such that number of pairs in each lag20, for example) Thank you Yadollah 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: The Estimation of Range paramter is very very big
Are you using some kind of automated fitting? The results would suggest that the model is inappropriate or that your basic assumptions are inappropriate. You should look at how the models are being fitted and what assumptions are made and question everything. Isobel Clark 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: Choosing Lag Distance and Angular Tolerance
Andrew You can apply 'standard' geostatistics if the measurements are the 'average' (or some similar feature) over an area. It makes interpeting the semi-variogram extremely tricky if you combine many different sizes of sample, but common sense is the main thing here. The trick is to derive a point semi-variogram model from which any size can be derived (see Chapter 3, Practical Geostatistics 1979, downloadable free from Web, http://uk.geocities.com/drisobelclark/practica.html) Kriging is modified to reflect that the samples are averages, mainly by changing the diagonal elements in the equations so that they are non-zero. I don't know any software package (off hand ) that does this, though. Isobel Clark --- Andrew Mullens [EMAIL PROTECTED] wrote: I have a question relating to this question, certainly not to question the previous writer, it just seems like a good time to bring it up. Will variograming and other such techniques work for the data the previous writer described, e.g samples aren't at points, but areas (and areas that might have very little to do with the question). If they did use points in the calculations where would the points be placed, at the center of the county, at the major population center, at some arbitrary point (e.g most northerly point). I may be miss reading the description, perhaps the sample are point samples, but were taken with one sample in each county. Obviously the point samples are never really point sample, they must be taken over some area, approximating a point, but does this design seem to push the boundaries on that assumption. Andrew - Original Message - From: Yadollah Waghei [EMAIL PROTECTED] To: [EMAIL PROTECTED] Cc: [EMAIL PROTECTED]; [EMAIL PROTECTED]; [EMAIL PROTECTED]; [EMAIL PROTECTED]; [EMAIL PROTECTED]; [EMAIL PROTECTED] Sent: Tuesday, May 15, 2001 7:33 AM Subject: AI-GEOSTATS: Choosing Lag Distance and Angular Tolerance Hello dears I have a spatial data set contaning n=262 observarion (The variable of interest is Rate of Tuberculosis in 262 counties of Iran). I want to fit some models to Directional semi-variograms,and then build anisotropic semi-variogram. Then questions are - Is there any rule for choosing Lag Distance and Angular Tolerance? -Also,how we can balance between Lag Distance and Angular Tolerance? -Do you agree that both must be very small,as possible?(Such that number of pairs in each lag20, for example) Thank you Yadollah 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 -- * 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 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
AI-GEOSTATS: Number of data points Variograms
Dear AI-GEOSTATiSticians, My research is on heavy metal pollution in water bodies. As a part of the analysis, I am doing kriging with the pollutant data. I have couple of problems in doing this task. 1. Though I have the data sets for 90 water bodies, most of them (85) have data points less than 10. As one can expect, this 'environment' gives trouble in fitting variograms. Two papers, I came across on similar issue haven't help me much in solving the problem. Is there any consistent tested way to approach such 'not-enough-data' situations? 2. Some data are with 'Hot Spots'. However, when I work with the data sets, I have the trouble in fitting the variogram. My questions may be trivial ones. How to distinguish Outliers from Hotspots, if there is a lack of site-information beyond the data set? Could it be possible to effectively fit variograms, when the hot spots are present? Could a variogram capture the hot spot presence for kriging? [ For most of the cases I tried with such suspected hotspot data, my results show that the linear interpolation works better than the krigged distribution based on the 'fitted' variograms] I would appreciate if anyone could provide me some suggestions on the above difficulties, and relevant references for my reading Thank you very much. Regards, -/Ramanitharan, K. = Ramanitharan Kandiah Graduate Student Department of Civil Environmental Engineering Tulane University New Orleans, LA 70125 USA. -- * 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: Number of data points Variograms
My research is on heavy metal pollution in water bodies. Hi, some thoughts (your numbering): (1) One of the things I have found successful is the following: construct your semi-variogram using ALL of your data but not allowing pairs between samples in different water bodies; use cross validation on each water body separately to see if the 'generic' model works for all of them or whether some are more variable or harder to predict than others; use the generic model for kriging with a variance/sill scaled for each water body. Is there any consistent tested way to approach such 'not-enough-data' situations? Not really, but I have found this works if the 'deposition' is similar in the various bodies. (2) 'Hot spots' are (a) erratic highs due to distribution being skewed or (b) true outliers (inhomogeneities). Which? Tackle accordingly. Cross validation will pick up outliers but not work properly if data is severely skewed. Could it be possible to effectively fit variograms, when the hot spots are present? Try calculating semi-variograms with and without 'hot spots' and see what happens. Kriging is based on an assumption of homogeneity and it is a little unfair to expect it to come back and say that's a daft thing to do ;-) [ For most of the cases I tried with such suspected hotspot data, my results show that the linear interpolation works better than the krigged distribution based on the 'fitted' variograms] I find this statement interesting. How do you define better -- prettier? nicer? easier to interpret? less polluted? Isobel Clark 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
