September
17, 2011 Posted by karmadsen under
blog, Geostatistics, Modeling Software, Statistics
2 Comments
In
attempting to find a rule of thumb for the minimum number of observation points
needed for kriging, I found out that it’s not particularly
straightforward. Kriging is a linear
least squares estimation algorithm. Even in simple least square regression there
is a lot of guess work involved in determining the minimum sample size needed
prior to conducting a study. Various
estimation methods exists to help researchers design regression analysis
studies based on the number of variables and the the desired power level. But in kriging, there are added levels of
complexity. The x,y distribution of
points matters (i.e. they shouldn’t all be clumped together). The volatility of the z-value matters (i.e.
you need more points to capture busy spatial trends).
