Updating Geological Codes Through Iterative Jack-Knife
Loading...
Date
Authors
Riquelme, Alvaro I.
Ortiz, Julian M.
Journal Title
Journal ISSN
Volume Title
Publisher
Queen's University
Abstract
We present a methodology to classify spatial data carrying only continuous variables into different categories, where categorical clustering is suitable to be applied to the data. The methodology is based in a very simple variation in the use of Bayes’ rule and the jack-knife technique. This study is mainly empirical, and is motivated by good results obtained during the application to a real case study.
Description
This is a preprint version of a paper that is or may be under consideration of publication. It does not contain changes and edits that will be made during peer review, or updates, edits and alterations by the authors and the publisher that may occur prior to acceptance and final publication.
Keywords
Citation
Riquelme AI, Ortiz JM (2019) Updating geological codes through iterative jack-knife, Predictive Geometallurgy and Geostatistics Lab, Queen’s University, Annual Report 2019, paper 2019-04, 41-53.