(original point by Gregoire:) > > > 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? >
(Anatoly:) > >what means "not sure"??? Pearson and Kolmogorov-Smirnov tests will be >used :-)) Anatoly, Chi2 and KS-tests also require binning the data, and different binning gives different p values, in general ! related questions: 1) the Weibull distribution can sometimes be used to describe datasets with heavy tails. (e.g., www.itl.nist.gov/div898/handbook/eda/section3/eda3668.htm ) However I don't know how to transform Weibull -> normal and back. Does somebody have experience ? 2) What is the effect of deviations of data from normal distr., in particular due to the presence of extrema (outliers, hot/cold spots), to structural analysis and to estimation, be it of kriging or simulation type ? regards, Peter ----------------------------------------------------- Peter Bossew European Commission (EC) Joint Research Centre (JRC) Institute for Environment and Sustainability (IES) TP 441, Via Fermi 1 21020 Ispra (VA) ITALY Tel. +39 0332 78 9109 Fax. +39 0332 78 5466 Email: [EMAIL PROTECTED] WWW: http://rem.jrc.cec.eu.int "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." + + 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/
