Likelihood Estimation with Incomplete Array Variate Observations

Missing data estimation is an important challenge with high-dimensional data arranged in the form of an array.In this paper we propose a probability model for partially observed multi-way array data. Fisher scoring and expectation maximization are used for estimation of the parameters of this distribution. The main application is to missing data imputation for multi way data.