1. A method for compressing multidimensional gaussian distributions with diagonal covariance matrices, the method comprising: clustering a plurality of gaussian distributions in a multiplicity of clusters for each dimension, wherein each cluster is represented by a centroid, and wherein each centroid and each gaussian distribution includes a mean and a variance, and wherein clustering includes: calculating a mean for each centroid as a weighted average of the means of the plurality of gaussian distributions forming the cluster; and calculating a variance for each centroid as function of a weighted average of the variances of the plurality of gaussian distributions forming the cluster.