Estimating Gaussian Copulas with Missing Data

2022/01/14 by Maximilian Kertel, Markus Pauly, Kertel, Maximilian +1
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Statistical Methods and Inference #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.2201.05565

Abstract

In this work we present a rigorous application of the Expectation Maximization algorithm to determine the marginal distributions and the dependence structure in a Gaussian copula model with missing data. We further show how to circumvent a priori assumptions on the marginals with semiparametric modelling. The joint distribution learned through this algorithm is considerably closer to the underlying distribution than existing methods.

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