Standard Errors and Speeding up Convergence
Geoffrey John McLachlan, Thriyambakam Krishnan · Wiley series in probability and statistics · 2008
This chapter contains sections titled: Introduction Observed Information Matrix Approximations to the Observed Information Matrix: I.I.D. Case Observed Information Matrix for Grouped Data Supplemented EM Algorithm Bootstrap Approach to Standard Error Approximation Baker's, Louis', and Oakes' Methods for Standard Error Computation Acceleration of the EM Algorithm via Aitken's Method An Aitken Acceleration-Based Stopping Criterion Conjugate Gradient Acceleration of EM Algorithm Hybrid Methods for Finding the Maximum Likelihood Estimate A Generalized EM Algorithm Based on One Newton-Raphson Step EM Gradient Algorithm A Quasi-Newton Acceleration of the EM Algorithm Ikeda Acceleration