Course Overview
This webinar introduces the power of non-linear geostatistics, including Multiple Indicator Kriging (MIK) and Conditional Expectation, and how these approaches better handle non-Gaussian, skewed data and complex grade distributions.
You will discover how these methods create a more realistic model of the deposit and assist in quantifying resources based on various cutoffs.
What you’ll learn:
- Why ordinary kriging can underestimate variability and lead to biased models.
- How non-linear methods better handle skewed, sparse, and non-Gaussian data.
- How MIK provide threshold-based modeling for better grade distribution insights.
- When and why to use Conditional Expectation in early-stage resource estimation.
- Real-world examples of how these tools in Isatis.neo improve early exploration decisions.
