Modeling Multivariate Density and Applications

@inproceedings{MalletRM2000,
 abstract = { Estimation of multivariate distributions from limited data sampling is an old problem in statistics and data analysis which still remains critical. In this paper we will present a new approach based on Discrete Smooth Interpolation which provide a large flexibility for handling different linear constrains. The results of this approach are compared with an classical kernel method. At the end we will present an application of 2D distribution on a conditional sequential simulation algorithm and we will see the differences of the results with the method known as ”Cloud Transform Simulation”. },
 author = { Mallet, Jean-Laurent AND Shtuka, Arben },
 booktitle = { 20th gOcad Meeting },
 month = { "june" },
 publisher = { ASGA },
 title = { Modeling Multivariate Density and Applications },
 year = { 2000 }
}