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.