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 >
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