Nonparametric Geostatistics

Nonfiction, Science & Nature, Science, Earth Sciences, Mathematics, Statistics
Cover of the book Nonparametric Geostatistics by S. Henley, Springer Netherlands
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Author: S. Henley ISBN: 9789400981171
Publisher: Springer Netherlands Publication: December 6, 2012
Imprint: Springer Language: English
Author: S. Henley
ISBN: 9789400981171
Publisher: Springer Netherlands
Publication: December 6, 2012
Imprint: Springer
Language: English

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.

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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.

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