How does fHMM process model parameters?

Lennart Oelschl├Ąger


In fHMM, four types of model parameters are estimated:

  1. non-diagonal elements (column-wise) gammas of transition probability matrices Gamma,

  2. expected values mus,

  3. standard deviations sigmas,

  4. degrees of freedom dfs.

All of these parameters have to fulfill constraints. Constrained parameters get the suffix Con, unconstrained parameters the suffix Uncon. Fine-scale parameters additionally get the suffix _star. Internally, collections of model parameters are processed using the following structures:

The package fHMM provides functions to transform these structures. Their names follow the logic x2y, where x and y are two structures.