Applied Geostatistics
Download Applied Geostatistics full books in PDF, epub, and Kindle. Read online free Applied Geostatistics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Applied Geostatistics
Author | : Edward H. Isaaks |
Publisher | : |
Total Pages | : 561 |
Release | : 1989 |
Genre | : Geology |
ISBN | : |
Download Applied Geostatistics Book in PDF, Epub and Kindle
Univariate description. Bivariate description. Spatial description. Data sets. Estimation. Random function models. Global estimation. Point estimation. Ordinary kriging. Block kriging. Search strategy. Cross validation. Cokriging. Estimating a distribution. Change of support. Assessing uncertainty. Final thoughts.
Applied Geostatistics Related Books
Language: en
Pages: 561
Pages: 561
Type: BOOK - Published: 1989 - Publisher:
Univariate description. Bivariate description. Spatial description. Data sets. Estimation. Random function models. Global estimation. Point estimation. Ordinary
Language: en
Pages: 302
Pages: 302
Type: BOOK - Published: 2011-04-14 - Publisher: Cambridge University Press
The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides
Language: en
Pages: 75
Pages: 75
Type: BOOK - Published: 2021-08-09 - Publisher: Springer Nature
This book explains the integration of data of different support in Geostatistics. There is a common misconception in the mining industry that the data used for
Language: en
Pages: 502
Pages: 502
Type: BOOK - Published: 1997 - Publisher: Oxford University Press, USA
This text provides an advanced introduction to the theory and applications of geostatistics, including tools for description, modeling spatial continuity, spati
Language: en
Pages: 276
Pages: 276
Type: BOOK - Published: 1997-05-13 - Publisher: Cambridge University Press
Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geost