Re: [AI-GEOSTATS: global vs local ordinary kriging]
Maybe it is worth pointing out that Ordinary Kriging with a 'global neighbourhood' (using all the points in simple speak) is the same as Simple Kriging with a neighbourhood which extends to the range of influence of the semi-variogram model (if any). Given this fact, you would be computationally safer to do Simple Kriging - otherwise known as kriging with known mean and saving yourself the problems of enormous and sparse matrix solutions. The only overhead to Simple Kriging is producing a reliable estimate of the global mean and, to be realistic, a standard error associated with it. Isobel Clark http://geoecosse.bizland.com/courses.htm Want to chat instantly with your online friends? Get the FREE Yahoo! Messenger http://uk.messenger.yahoo.com/ -- * 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: global vs local ordinary kriging
Ulrich Leopold wrote: Dear list, What would you consider the most reliable ordinary kriging estimate? To use a local search neighbourhood (slightly bigger than the effective range) or set to global to include *all* data locations? Ulrich Depending on the strength of spatial correlaton and block size. If blocks are small and spatial correlation strong, the difference may be negligible. If blocks are large, relative to the domain, I would choose large neighbourhoods. In case of weak spatial correlation, you're basically estimating a local or global mean; so it depends on what you want for result: local or global mean values. -- Edzer -- * 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: global vs local ordinary kriging
Ulrich Depends how powerful your computer is, what algorithm you use to solve equations and how many data you have. Isobel http://geoecosse.bizland.com/0toKriging.htm Want to chat instantly with your online friends? Get the FREE Yahoo! Messenger http://uk.messenger.yahoo.com/ -- * 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: global vs local ordinary kriging
Hi Ulrich, It's not an easy question. First note that the search strategy includes not only the size of the search window but also the maximum number of observations. In may occasions, I set the search radius to a very large distance and use the number of observations as the controling parameter. Using too many observations or too large search windows may lead to oversmoothing, while estimates based on low number of observations (say less than 8 in 2D) might not be very reliable. Of course it depends also on the relative nugget effect. If it is large, even further away observations will receive a significant weight. In practice, global search windows are seldom used because: (1) no reliable semivariogram values are available for so large distances, (2) the size of the kriging system is likely very large, and (3) the stationarity assumption within the search window might become questionable. The best way to proceed would be to do some cross validation using various search strategies and investigate their impact on re-estimation scores. Regards, Pierre Goovaerts 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 8 Jul 2003, Ulrich Leopold wrote: Dear list, What would you consider the most reliable ordinary kriging estimate? To use a local search neighbourhood (slightly bigger than the effective range) or set to global to include *all* data locations? Ulrich -- __ Ulrich Leopold MSc. Department of Physical Geography Institute for Biodiversity and Ecosystem Dynamics Faculty of Science University of Amsterdam Nieuwe Achtergracht 166 NL-1018WV Amsterdam Phone: +31-(0)20-525-7456 (7451 Secretary) Fax: +31-(0)20-525-7431 Email: [EMAIL PROTECTED] http://www.frw.uva.nl/soil/Welcome.html Check us also out at: Netherlands Centre for Geo-ecological Research http://www.frw.uva.nl/icg -- * 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
