The fundamental result on the rate of convergence of the EM algorithm has proven to be theoretically valuable and practically useful. Here, this result is generalized to the ECM algorithm, a more flexible and applicable iterative algorithm proposed recently by Meng and Rubin. Results on the rate of convergence of variations of ECM are also presented. An example is given to show that intuitions accurate for complete-data iterative algorithms may not be trustworthy in the presence of missing data.
"On the Rate of Convergence of the ECM Algorithm." Ann. Statist. 22 (1) 326 - 339, March, 1994. https://doi.org/10.1214/aos/1176325371