A 0:46 +0100 19/12/01, Marcus Schneider a �crit: >[...] help me to find appropriate data or point me to something helpful...
I always consider as very useful, if not a necessary step, to built a fully hand-made (or brain-made :-)) set of "data", with all the characteristics well known, because you monitor them, except maybe some part of random noise or probability driven parameters (e.g. it could be the locations of sampling). So, your statistical treatment(s) should be able to find what you know being there ! Moreover, a priori sensitivity analysis is, from that point, and specially if your test set of data is somehow "not too far" from the real sets of data, just the next step, with systematics or Monte Carlo repeated variations of the same procedure. >Last I have to apologize fo my bad english. So do I ! --�ric +=[ �ric LEWIN <mailto:[EMAIL PROTECTED]> T�l: (33/0)4 76 63 59 13 ]=+ | \ >>>>> LGCA <<<<< / | | === OSUG === \ Labo. de G�odynamique / === UJF === | | Observatoire des Sciences \ des Cha�nes Alpines / Universit� Joseph | += de l'Univers de Grenoble ===\= Grenoble (France) =/== Fourier, Grenoble-1 =+ -- * 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. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
