RE: [ai-geostats] Sum of predicted values
- Hi Pete,
This is a classical example where stochastic simulation would allow an easy quantification
of the uncertainty attached to the aggregated value. Just generate a series of realizations
of your process over these 1700 points, sum each set of simulated values, and
use the empirical distribution of simulated block values as a model of uncertainty.
You can find an example in Goovaerts, P. 2001. Geostatistical modelling of uncertainty in soil science. Geoderma, 103: 3-26. <http://www.terraseer.com/training/geostats/geoder01.pdf> that you can download from my webpage.
From: Pete Gething [mailto:P.W.GETHING@...]
Sent: Mon 8/1/2005 9:30 AM
Subject: [ai-geostats] Sum of predicted values
I have Kriged predictions of a continuous variable at a set of 1700 points. I want to sum these values and obtain an estimate of the overall prediction variance based on the kriging variances of the individual points (i.e., taking into account the spatial correlation between points). The data are approximately Gaussian.
I would expect there to be a standard solution to this problem, but I'm having difficulty finding examples - can anyone help me out, or point me to a reference?
Thanks in advance,
School of Electronics and Computer Science
School of Geography
University of Southampton
Southampton SO17 1BJ
Tel: +44 (0) 23 8059 2013