. Author manuscript; available in PMC: 2016 Feb 11.

Published in final edited form as: Ann Appl Stat. 2010 Jun;4(2):764–790. doi: 10.1214/09-AOAS314

Algorithm 3.

Alternating Conditional Expectations Algorithm.

Initialize ${\hat{X}}_{i, j}^{(0)} = {\hat{ν}}_{i} + {\hat{μ}}_{j}$ for X_i,j ∈ X_m.
For each row, i, with missing values:
1. Set ${\hat{X}}_{i, m_{i}}^{(k + 1)} = E (X_{i, m_{i}} | X_{i, o_{i}}^{(k)}, X_{\neq i, r}^{(k)})$ .
For each column, j, with missing values:
1. Set ${\hat{X}}_{m_{j}, j}^{(k + 1)} = E (X_{m_{j}, j} | X_{o_{j}, j}^{(k)}, X_{c, \neq j}^{(k)})$ .
Repeat Steps 1 and 2 until convergence.