Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semimartingale dynamics and estimation for a semi-Markov chain   We consider a finite state discrete time process X. Without loss of
generality the finite state space can be identified with the set of unit
vectors {e1, e2, . . . , eN} with ei = (0, . . . , 0, 1, 0, . . . , 0)0 2 RN.
For a Markov chain the times the process stays in any state are geometrically
distributed. This condition is relaxed for a semi-Markov chain. We first derive
the semimartingale dynamics for a semi-Markov chain. We then consider the
situation where the chain is observed in noise. We suggest how to estimate the
occupation times in the states and derive filters and smoothers for quantities
associated with the chain.

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The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an