Re: AI-GEOSTATS: sparse data problem
Gail Sorry for not responding earlier to your request. Your explanatory comment to Monica does not convince me as a exploration and mining geologist. I think her comments are wise and should be considered. A 20x30 km area is a large one even when dealing with very uniform geology. Even in such conditions, different properties may be encountered, either as faults, vein or fracturation system, small intrusive bodies, mineral showings or deposits, pollution zones, etc. Such a small sample set as you have ["few (5-6) original data points + interpolated external data"] that covering whole study area] does not allow you to really appraise the validity and/or the geological cause of this "outlier." (There might be a sampling or assaying cause also). In such a case, it should be shown as an anomaly, not averaged out or kriged out. Excluding sampling/analytical problems, the outlier only has a "detection"value, meaning that the geology is not as uniform as expected and that additional geological observations and sampling in the vicinity is required to elucidate this problem. We should view geostatistics as an ancillary tool to understand a two or three dimensional "geological universe." Whenever data ara as sparse as in your exemple, kriged values should not replace and/or eliminate the potential meaning of sparse field observations. Sincerely Marcel Vallée Marcel Vallée Eng., Geo. Géoconseil Marcel Vallée Inc. 706 Routhier St Québec, Québec, Canada G1X 3J9 Tel: (1) 418, 652, 3497 Email: [EMAIL PROTECTED] = Gali Sirkis wrote: Hi Monica, thanks for quick reply. The interpolated data is a different data set with is by its nature (speaking about geological properties) should be correlated with the sparse one. This is a geological data over not huge area - around 20x30 kilometers. It should have at least some spatial correlation. The variogram is not of striking beauty :) but it is not a pure nugget effect, though. The only other way meaningfully interpolate between those sparse points, it seems to use the simple linear regression between those two datasets. The literature about kriging/interpolating for very sparse data would definitely help, if anybody know about, please let know. Thanks, Gali --- Monica Palaseanu-Lovejoy <[EMAIL PROTECTED]> wrote: Hi, I am not sure i understood correctly your question. Fist of all, do the interpolated data have come from your sparse data interpolation? What method of interpolation did you use in this case? After Burrough and McDonnel, 2000, you need at least 50 points to have reliable results through kriging. Certainly you can do it on less data, but until now i never saw a study considering this problem in depth (maybe there is literature out there, and if it does and anybody knows about it - i would like to know it also ;-)) Secondly, if you know the outlier is not an error, but you interpret it as representing a different combination of properties than the rest of your data - i am not very sure it is wise to use it together with your rest of the data in any interpolation exercise. The outlier may represent a different population and in this case i cannot see any "physical" reason to treat all your data together if parts of the data represent different things. At least this is my opinion. Besides, if your data is not only sparse (5 or 6 data points it is really very sparse i think) but also far away in space, they can be at distances grater than the spatial correlation range, and in this case i really don't think you can use kriging you will have either a pure nugget effect or a very high nugget value and not a too high spatial correlation. Monica Dear list members, Please advise what to do in following case: The sparse dataset for kriging inlcudes only few (5-6) original data points + interpolated external data, that covering whole study area. One of the original data points seems completly not to fit to the main correlation line between original and external data, however mostly probable is not an error, but might represent different combination of data properties. Is there is any chance to use this outlying point? Does is sound feasible for you as specialists in statistical analysis to use the kriging method in this case? Many thanks in advance for your help, Gali Sirkis > __ Do you Yahoo!? Free Pop-Up Blocker - Get it now http://companion.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: sparse data problem
Thank you Umberto, this definitely sounds as an interesting solution. Can you advise something to read about this method? thanks again, Gali --- Umberto Fracassi <[EMAIL PROTECTED]> wrote: > Hi Gali, > > may you not try with Radial Basis Function > (Multiquadric) instead of > kriging? It's meant to be an exact interpolator, > although sometimes it > doesn't fully honor your data. However, it's based > on the concept of > track data which seems to me to suit the issue you > mention. I employ RBF > with macroseismic effects of historical earthquakes. > Since these data > are sparse (and scarce and scattered..!) by > definition, this algorithm > effectively pursues aligned pattern in the dataset. > > Hope this may help... > > Ciao and best regards, > > > Umberto > > Gali Sirkis wrote: > > >Dear list members, > > > >Please advise what to do in following case: > > The sparse dataset for kriging inlcudes only few > >(5-6) original data points + interpolated external > >data, that covering whole study area. > >One of the original data points seems completly not > to > >fit to the main correlation line between original > and > >external data, however mostly probable is not an > >error, but might represent different combination of > >data properties. > >Is there is any chance to use this outlying point? > >Does is sound feasible for you as specialists in > >statistical analysis to use the kriging method in > this > >case? > > > >Many thanks in advance for your help, > > > >Gali Sirkis > > > >__ > > > > > > > > -- > > > Umberto Fracassi > > > Istituto Nazionale di Geofisica e Vulcanologia > Via di Vigna Murata, 605 > 00143 Roma > Italy > Tel:+39-06-51860557 > Fax:+39-06-5041181 > Email: [EMAIL PROTECTED] > WWW:http://www.ingv.it/paleo/fracassi/ > > * > "This is what you should do: Love the earth and the > sun and the animals, despise riches, give alms to > everyone that asks, stand up for the stupid and > crazy, devote your income and labor to others, hate > tyrants, argue not concerning god, have patience and > indulgence toward people, take off your hat to > nothing known or unknown, or to anyone or number of > people reexamine all you have been told at > school or church, or in any book, dismiss what > insults your soul, and your very flesh shall be a > great poem." > > Walt Whitman > * > > > > > > -- > * 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!? Free Pop-Up Blocker - Get it now http://companion.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: sparse data problem
Hi Monica, thanks for quick reply. The interpolated data is a different data set with is by its nature (speaking about geological properties) should be correlated with the sparse one. This is a geological data over not huge area - around 20x30 kilometers. It should have at least some spatial correlation. The variogram is not of striking beauty :) but it is not a pure nugget effect, though. The only other way meaningfully interpolate between those sparse points, it seems to use the simple linear regression between those two datasets. The literature about kriging/interpolating for very sparse data would definitely help, if anybody know about, please let know. Thanks, Gali --- Monica Palaseanu-Lovejoy <[EMAIL PROTECTED]> wrote: > Hi, > > I am not sure i understood correctly your question. > Fist of all, do > the interpolated data have come from your sparse > data > interpolation? What method of interpolation did you > use in this > case? > > After Burrough and McDonnel, 2000, you need at least > 50 points to > have reliable results through kriging. Certainly you > can do it on less > data, but until now i never saw a study considering > this problem in > depth (maybe there is literature out there, and if > it does and > anybody knows about it - i would like to know it > also ;-)) > > Secondly, if you know the outlier is not an error, > but you interpret it > as representing a different combination of > properties than the rest > of your data - i am not very sure it is wise to use > it together with > your rest of the data in any interpolation exercise. > The outlier may > represent a different population and in this case i > cannot see any > "physical" reason to treat all your data together if > parts of the data > represent different things. At least this is my > opinion. > > Besides, if your data is not only sparse (5 or 6 > data points it is > really very sparse i think) but also far away in > space, they can be > at distances grater than the spatial correlation > range, and in this > case i really don't think you can use kriging > you will have either > a pure nugget effect or a very high nugget value and > not a too high > spatial correlation. > > Monica __ Do you Yahoo!? Free Pop-Up Blocker - Get it now http://companion.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: sparse data problem
Hi, I am not sure i understood correctly your question. Fist of all, do the interpolated data have come from your sparse data interpolation? What method of interpolation did you use in this case? After Burrough and McDonnel, 2000, you need at least 50 points to have reliable results through kriging. Certainly you can do it on less data, but until now i never saw a study considering this problem in depth (maybe there is literature out there, and if it does and anybody knows about it - i would like to know it also ;-)) Secondly, if you know the outlier is not an error, but you interpret it as representing a different combination of properties than the rest of your data - i am not very sure it is wise to use it together with your rest of the data in any interpolation exercise. The outlier may represent a different population and in this case i cannot see any "physical" reason to treat all your data together if parts of the data represent different things. At least this is my opinion. Besides, if your data is not only sparse (5 or 6 data points it is really very sparse i think) but also far away in space, they can be at distances grater than the spatial correlation range, and in this case i really don't think you can use kriging you will have either a pure nugget effect or a very high nugget value and not a too high spatial correlation. Monica -- * 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: sparse data problem
Hi Gali, may you not try with Radial Basis Function (Multiquadric) instead of kriging? It's meant to be an exact interpolator, although sometimes it doesn't fully honor your data. However, it's based on the concept of track data which seems to me to suit the issue you mention. I employ RBF with macroseismic effects of historical earthquakes. Since these data are sparse (and scarce and scattered..!) by definition, this algorithm effectively pursues aligned pattern in the dataset. Hope this may help... Ciao and best regards, Umberto Gali Sirkis wrote: Dear list members, Please advise what to do in following case: The sparse dataset for kriging inlcudes only few (5-6) original data points + interpolated external data, that covering whole study area. One of the original data points seems completly not to fit to the main correlation line between original and external data, however mostly probable is not an error, but might represent different combination of data properties. Is there is any chance to use this outlying point? Does is sound feasible for you as specialists in statistical analysis to use the kriging method in this case? Many thanks in advance for your help, Gali Sirkis __ -- Umberto Fracassi Istituto Nazionale di Geofisica e Vulcanologia Via di Vigna Murata, 605 00143 Roma Italy Tel:+39-06-51860557 Fax:+39-06-5041181 Email: [EMAIL PROTECTED] WWW:http://www.ingv.it/paleo/fracassi/ * "This is what you should do: Love the earth and the sun and the animals, despise riches, give alms to everyone that asks, stand up for the stupid and crazy, devote your income and labor to others, hate tyrants, argue not concerning god, have patience and indulgence toward people, take off your hat to nothing known or unknown, or to anyone or number of people reexamine all you have been told at school or church, or in any book, dismiss what insults your soul, and your very flesh shall be a great poem." Walt Whitman * -- * 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