Adapting the EM Algorithm

Grung and Manne [11] studied the EM algorithm in the case of missing values. Experiments showed a faster convergence compared to the iterative imputation algorithm. The computational complexity is $O(Nc^2+nc^3)$ per iteration, where $N$ is the number of observed values, assuming naïve matrix multiplications and inversions but exploiting sparsity. This is quite a bit heavier than EM with complete data, whose complexity is $O(ndc)$ [7] per iteration.