Nonparametric Geostatistics

S. Henley

ISBN 10: 0853349770 / ISBN 13: 9780853349778

Verlag: Springer Netherlands, Springer Netherlands Okt 1981, 1981

Beschreibung

Neuware -The ideas in this book have been developed over the past three or four years while I was working at the Institute of Geological Sciences and later for Golder Associates. During that time all of the geological modelling and resource estimation studies I participated in had data that were non-ideal in one respect or another (or just plain 'dirty'): the standard ways of handling the data with kriging or with simpler parametric methods gave reason able results, but always there were nagging doubts and some lack of confidence because of the corners that had to be cut in generat ing a model. The bimodal distribution that was assumed to be 'close enough' to normal; the pattern of rich and poor zones that was not quite a trend yet made the data very non-stationary; and the many plotted variograms that would not fit any standard model variogram: these all contributed to the feeling that there should be something that statistics could say about the cases where hardly any assumptions could be made about the properties ofthe parent population.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 164 pp. Englisch.

Bestandsnummer des Verkäufers 9780853349778

Bibliografische Details

• Titel: Nonparametric Geostatistics
• Verlag: Springer Netherlands, Springer Netherlands Okt 1981
• Erscheinungsjahr: 1981
• Sprache: Englisch
• ISBN-10: 0853349770
• ISBN-13: 9780853349778
• Einband: Buch
• Zustand: Neu
• Abmessungen: 241B x 160 H x 14 T Millimeter Breite: 241 mm, Höhe: 160 mm, Tiefe: 14 mm
• Gewicht: 418 Gramm

Über diesen Titel

Inhaltsangabe

The ideas in this book have been developed over the past three or four years while I was working at the Institute of Geological Sciences and later for Golder Associates. During that time all of the geological modelling and resource estimation studies I participated in had data that were non-ideal in one respect or another (or just plain ’dirty’): the standard ways of handling the data with kriging or with simpler parametric methods gave reason­ able results, but always there were nagging doubts and some lack of confidence because of the corners that had to be cut in generat­ ing a model. The bimodal distribution that was assumed to be ’close enough’ to normal; the pattern of rich and poor zones that was not quite a trend yet made the data very non-stationary; and the many plotted variograms that would not fit any standard model variogram: these all contributed to the feeling that there should be something that statistics could say about the cases where hardly any assumptions could be made about the properties ofthe parent population.