Dear Chaosheng Zhang
This problem can be looked in various perspectives. You have to fit the data in the broader picture and objectives. First, what do your soil samples represent? How were they collected, what was their size? Are they spot samples, multiple takes in a cross pattern with x metres between takes up to y meters away from the centre? Etc.? A significant part of nuggets effects when dealing with rock or soil materials may be sampling and sample preparation generated. If these samples were assayed by AA, what was the size of the portion used? If one gram, it is much more liable to generating a nugget effect than with 5 or 10 grams whenever pulverisation size was not fine enough and uniform. Second, what is the purpose of your study. Academic work? Detection, remediation- restoration, etc.? The high values might have physical significance in the later perspective and smothing them may not be the ideal solution. Lead and Arsenic contamination cannot be neglected or minimized. In an industry or regulation perspective, the recommendation in that case might be to to carry out additional sampling around the hot spots to delineate them better, say samples at 100 m spacing, as well as checking the original hot spots, with a sampling method designed to be representative. I am afraid I may not be easing you out of your problem, but such is physical reality. Chapter 8 in Jeff Myer's book "Geostatistical Error Management," deals with sampling and Chapter 16 with sampling strategy. I published a text on "Sampling Quality Control" in a mineral exploration and development perspective in Exploration and Mining Geology, Vol 7, No 1-2, p. 107-116 (1998). This issue has several other papers on sampling. If it is not available to you, I could send you a file copy of my paper. Cheers Marcel Vallée Geoconseil Marcel Vallée Inc. 706 Routhier Ave Québec, Québec G1X 3J9 Canada Tel: (1) 418 652 3497 Fax: (1) 418 652 9148 Email: [EMAIL PROTECTED] ================================================ 14/12/01 06:33:35, Chaosheng Zhang <[EMAIL PROTECTED]> wrote: >Dear Marcel Vallée, > >Thanks. I think the sampling density is good enough to reveal the spatial >structure, and the extreme samples are located within the "hot spots". The >problem is that the few values are still extremely high within the "hot >spots". This may be what the "nugget effect" means. > >I'm just wondering if these few extreme values should really be "discarded"/ >"censored" or replaced. However, this could get some criticism as they may >be "real". > >If it is hard to find the best way, I will have to "replace" all the extreme >values with 99% or 98% percentiles. But I'm not sure if it is appropriate to >do so. > >Cheers, > >Chaosheng Zhang > > >----- Original Message ----- >From: "Marcel Vallée" <[EMAIL PROTECTED]> >To: <[EMAIL PROTECTED]>; "Chaosheng Zhang" <[EMAIL PROTECTED]> >Sent: Thursday, December 13, 2001 10:40 PM >Subject: Re: AI-GEOSTATS: Extreme values? > > >> >> Dear Chaosheng Zang >> >> The sampling interval is so wide that the high values could easily be >>related to "hot spots" of >> higher grade contamination, i..e dumping areas for particular kinds of >>slags, mineralized waste, etc. A property map might help. >> >> Have you contoured the data? If so, the sampling interval is so wide that >>real hot spots of >> environmental significance might not show 2D distribution on such a wide >sampling grid, however. >> >> Regards >> >> Marcel Vallée, Eng,, Geo. >> Geoconseil Marcel Vallée Inc. >> 706 Routhier Ave >> Québec, Québec G1X 3J9 >> Canada >> Tel: (1) 418 652 3497 >> Fax: (1) 418 652 9148 >> Email: [EMAIL PROTECTED] >> >> ============================================== >> 13/12/01 08:01:48, Chaosheng Zhang <[EMAIL PROTECTED]> wrote: >> > >> > Date: Thu, 13 Dec 2001 13:01:48 +0000 >> > >> > From: Chaosheng Zhang <[EMAIL PROTECTED]> >> > Subject:AI-GEOSTATS: Extreme values? >> > To: [EMAIL PROTECTED] >> > >> > Dear all, >> > >> > My question is: How to deal with the extreme/outlying values in a data >>>set? >>> >> > I am dealing with heavy metal concentrations in soils from a mine area. >>>The sample number is 223, and the samples are spatially evenly distributed >>>with the sampling interval of 400 metres. There are several samples with >>>extremely high values, which makes me feel uncomfortable. The >>>percentiles of the dataset are listed as follows (in mg/kg): >> > >> > >> > Zn Cu Pb Cd As >> > Min 4 1 25 0.0 2 >> > 5% 35 6 35 0.1 6 >> > 10% 40 7 41 0.2 7 >> > >> > 25% 65 13 62 0.3 9 >> > 50% 122 18 168 0.6 15 >> > 75% 338 27 821 1.5 28 >> > 90% 907 56 2799 2.8 58 >> > >> > 95% 1986 116 4490 4.2 80 >> > 96% 2462 151 4698 4.9 82 >> > 97% 3493 178 5413 6.2 91 >> > 98% 4697 207 7609 8.3 111 >> > >> > 99% 6712 247 11750 12.4 184 >> > Max 11473 1293 16305 48.5 1060 >> > When doing geostatistical and statistical analyses, we need some confidence >> > in dealing with the these very high extreme values which account for less >> > than 2% of the total sample number. >> > >> > Any suggestions? >> > >> > Cheers, >> > >> > Chaosheng Zhang >> > =================================== >> > Dr. Chaosheng Zhang >> > Department of Geography >> > National University of Ireland >> > Galway >> > IRELAND >> > >> > Tel: +353-91-524411 ext. 2375 >> > Fax: +353-91-525700 >> > Email: [EMAIL PROTECTED] >> > =================================== >> >> >> >> >> -- >> * 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. 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