Dear list In addition to the excellent points made by Isobel, others from Anatoly are given below. I went through the archives of ai-geostats and found back very interesting discussions on this point (I apparently asked a similar question in 2001, and 2003, ... I definitely have a poor memory). As pointed here again, the nscore transform is probably interesting only if the are many data, enough at least to draw a clear histogram.
Having in mind a paper of Evan Englund in which 6 back-transforms are compared in a case study involving lognormal kriging, I would personally be tempted to go directly for a nscore transform to avoid myself asking questions on the consequences of the back transform (I also most frequently deal with datasets with so called "hot spots", i.e. very skewed datasets for which the lognormal transform may not be sufficient). I admit the nscore back-transform remains almost at the level of a magic button to me and that I am discarding warnings like those made in Saito and Goovaerts (Geostatistical interpolation of positively skewed and censored data in a dioxin contaminated site. Environmental Science & Technology, 2000, vol.34, No.19: 4228-4235) in which a straight back-transform of the nscore estimates would lead to biased estimates. Still, I suspect the "lognormal kriging" reflex to be some behaviour conditioned by the mining field while other disciplines focusing on extreme values may be less receptive to the approach and go directly for the more appealing (at first sight) nscore transform. Best regards, Gregoire PS: Speaking now as the moderator of ai-geostats, please send replies to the list, not to the author of the question. This should further contribute to letting the archives grow. __________________________________________ Gregoire Dubois (Ph.D.) European Commission (EC) Joint Research Centre Directorate (DG JRC) WWW: http://www.ai-geostats.org "The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission." -----Original Message----- From: Anatoly Saveliev [mailto:[EMAIL PROTECTED] Sent: 10 August 2006 11:42 To: [EMAIL PROTECTED] Subject: Re: AI-GEOSTATS: Log versus nscore transform Dear Gregoire, > > I am puzzled about the use of logarithmic and nscore transforms in geostatistics. > > Given the apparent advantages in using nscore transforms over the logarithmic transform (nscore has no problem when dealing with 0 values and is "managing" the tails of the distribution very (more?) efficiently), why would one still want to use log-normal kriging? Because of the mathematical elegance of using a model only? not only ... - a lot of the known variables in geology, ecology and more widely in the Earth science have log-normal distribution: they are limited by the zero (or phone values) at the left end, and are unlimited at the right end of the domain. - nscore is histogram-based, and as that it need a lot of data for the robust histogram estimation. - I'm not agree that nscore ""managing" the tails of the distribution very (more?) efficiently". As a rule, we haven't enough data at the left and especialy at the righ sides of the values domain, so we need to guess the tails (two guesses instead of one for the log()). - log-transfom have a close form, so all the data are used in the transform fit. Zeros are not a problem since Y'=log(a+b*Y) or Y'=sign(Y)*log(a+b*|Y|) is used. nscore is locally interpolated (and extrapolated at the sides), so it is less robust. > Moreover, one can frequently not be "sure" about the lognormality of the analysed dataset, so why would one still take the risk of using log-normal kriging? what means "not sure"??? Pearson and Kolmogorov-Smirnov tests will be used :-)) > Thank you in advance for any feedback on this issue. Best regards, Anatoly Saveliev, Kazan State University, Russia + + To post a message to the list, send it to [email protected] + To unsubscribe, send email to majordomo@ jrc.it with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
