I believe a related topic is called the proportional effect, which is
displayed when populations
display related, but different properties, as discussed in Geostatistical
Ore Reserve Estimation,
M. David, pp170, which also displays itself in a sudy of the normal and
relative variograms.
Regards
Every resource model I have done, I always subdivide the populations into
those of equal mean and variance, so stationarity is obeyed, is this the
correct
procedure, I havn't read Mining Geostatisitcs in detail yet, but understood
that this was a basic requirement for geostatisitical modelling pro
Colin,
Isn't a basic rule of geostatisitics that all populations must follow the
intrinsic
hypothesis, i.e. stationarity ,constant mean and variance, so you should
split
any populations that do not have the same mean and variance, introduced
pp33 Mining Geostatistics A.G.Journel & Ch. J.Huijbregts.
Most of the tests of hypotheses that have been mentioned recently on this list
serv are non-spatial, i.e., there is nothing in the underlying statistical
assumptions that specifically pertains to spatial data. The one common
assumption is "random sampling" or "iid" (independent, identically
distr
Sorry if this is somewhat off subject - but I'd like to discuss (and invite
further comments) on Colin's comments regarding the effects of independence
on standard statistical tests.
He mentioned that a lack of independence "typically removes a large part of
the usability of basic tests unless c
Hello,
I am currently principal investigator on a major NIH grant
that aims to develop software for test of hypothesis
using alternate hypothesis specified by the user and that
differ from the omnibus "spatial independence";
we called them "spatial neutral models".
For example, you can test for cl
Hence my recommendation to use cross cross validation
Isobel
http://geoecosse.bizland.com/books.htm
--- Colin Daly <[EMAIL PROTECTED]> wrote:
>
>
> Hi
>
> Sorry to repeat myself - but the samples are not
> independent. Independance is a fundamental
> assumption of these types of tests - an
Title: RE: [ai-geostats] F and T-test for samples drawn from the same p
Hi
Sorry to repeat myself - but the samples are not independent. Independance is a fundamental assumption of these types of tests - and you cannot interpret the tests if this assumption is violated. In the situation w
Dear all,
I'm wondering if sample size (number of samples, n)
is playing a role here.
Since Colin is using Excel to analyse several
thousand samples, I have checked the functions of t-tests in Excel. In the Data
Analysis Tools help, a function is provided for "t-Test: Two-Sample
