Summary
In this paper we consider a hidden discrete time finite state process X whose behavior at the present time t depends on its behavior at the previous k time steps, which is a generalization of the usual hidden finite state Markov chain, in which k equals to one. We consider the case when the range space of our observations is finite. We present filtering equations for certain functionals of the chain and perform related error analysis.
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© 2007 Springer Science+Business Media, LLC
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Luo, S., Tsoi, A.H. (2007). Filtering of Hidden Weak Markov Chain -Discrete Range Observations. In: Mamon, R.S., Elliott, R.J. (eds) Hidden Markov Models in Finance. International Series in Operations Research & Management Science, vol 104. Springer, Boston, MA. https://doi.org/10.1007/0-387-71163-5_7
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DOI: https://doi.org/10.1007/0-387-71163-5_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-71081-5
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