Dear Isobel, Thanks for the information. Perhaps I didn't explain my request clearly. What I need is to verify the ideas you suggested in the previous message. Specifically, (1) Has anybody used the sill values (in geostatistics) to replace the variances (in classical statistics) in F test? (2) Has anybody used the global standard errors (in geostatistics) to replace the mean standard errors (in classical statistics) in t-test?
Cheers, Chaosheng ----- Original Message ----- From: "Isobel Clark" <[EMAIL PROTECTED]> To: "Chaosheng Zhang" <[EMAIL PROTECTED]> Cc: <[EMAIL PROTECTED]> Sent: Monday, December 06, 2004 6:03 PM Subject: [ai-geostats] Re: F and T-test for samples drawn from the same p > There ws a pretty good paper on global standard errors > in the 1984 APCOM proceedings, so I am sure it should > be in the major textbooks by now. > > Commparing the sills is very straightforward, I think. > > Isobel > http://geecosse.bizland.com/books.htm > > --- Chaosheng Zhang <[EMAIL PROTECTED]> > wrote: > > Isobel, > > > > Good idea, and that's a step forward. Any references > > or is it still an idea? > > > > Cheers, > > > > Chaosheng > > > > ----- Original Message ----- > > From: "Isobel Clark" <[EMAIL PROTECTED]> > > To: "AI Geostats mailing list" <[EMAIL PROTECTED]> > > Sent: Monday, December 06, 2004 1:07 PM > > Subject: Re: [ai-geostats] F and T-test for samples > > drawn from the same p > > > > > > > Dear all > > > > > > I am having difficulty understanding why none of > > you > > > want to try a spatial approach to statistics. > > Everyone > > > is trying to make the 'independent' statistical > > tests > > > work on spatial data. Try turning this around and > > look > > > at the spatial aspect first. > > > > > > (1) Testing variances: the sill on the > > semi-variogram > > > (total height of model) is theoretically a good > > > estimate for the sample variance when > > auto-correlation > > > or spatial dependence is present. Do your F test > > on > > > that. Yes, you still have degrees of freedom > > problems, > > > but with thousands of samples the 'infinity > > column' > > > should be sufficient. > > > > > > (2) Testing means: the classic t-test in the > > presence > > > of 'equal variances' requires the 'standard error' > > of > > > each mean. For independent samples, this is > > s/sqrt(n). > > > For spatially dependent samples, this is the > > kriging > > > standard error for the global mean. Your only > > problem > > > then is getting a global standard error. > > > > > > Isobel > > > http://geoecosse.bizland.com/whatsnew.htm > > > > > > > > > > > > > -------------------------------------------------------------------------- -- > > ---- > > > > > > > * By using the ai-geostats mailing list you agree > > to follow its rules > > > ( see > > http://www.ai-geostats.org/help_ai-geostats.htm ) > > > > > > * To unsubscribe to ai-geostats, send the > > following in the subject or in > > the body (plain text format) of an email message to > > [EMAIL PROTECTED] > > > > > > Signoff ai-geostats > > > > > > > > > > * By using the ai-geostats mailing list you agree > to > > follow its rules > > ( see > > http://www.ai-geostats.org/help_ai-geostats.htm ) > > > > * To unsubscribe to ai-geostats, send the following > > in the subject or in the body (plain text format) of > > an email message to [EMAIL PROTECTED] > > > > Signoff ai-geostats > > ---------------------------------------------------------------------------- ---- > * By using the ai-geostats mailing list you agree to follow its rules > ( see http://www.ai-geostats.org/help_ai-geostats.htm ) > > * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] > > Signoff ai-geostats >
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