Estimation of Conditional Distributions using Gaussian Mixture Models

This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations. The data set used is a part of the digital elevation model of Switzerland.


Year:
2002
Publisher:
IDIAP
Keywords:
Note:
Submitted to ICANN 2002
Laboratories:




 Record created 2006-03-10, last modified 2018-03-17

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