We derive the observed information matrix of hidden Markov models by the application of the Oakes (1999)’s identity. The method only re quires the first derivative of the forward-backward recursions of Baum and Welch (1970), instead of the second derivative of the forward recursion, which is required within the approach of Lystig and Hughes (2002). The method is illustrated by an example based on the analysis of a longitudinal dataset which is well known in sociology.
Bartolucci, F., Farcomeni, A., Pennoni, F. (2012). A note on the application of the Oakes’ identity to obtain the observed information matrix of hidden Markov models [Working paper].
A note on the application of the Oakes’ identity to obtain the observed information matrix of hidden Markov models
PENNONI, FULVIA
2012
Abstract
We derive the observed information matrix of hidden Markov models by the application of the Oakes (1999)’s identity. The method only re quires the first derivative of the forward-backward recursions of Baum and Welch (1970), instead of the second derivative of the forward recursion, which is required within the approach of Lystig and Hughes (2002). The method is illustrated by an example based on the analysis of a longitudinal dataset which is well known in sociology.
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