Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Expectation-Maximization Algorithm for Continuous-time Hidden Markov
  Models   We propose a unified framework that extends the inference methods for
classical hidden Markov models to continuous settings, where both the hidden
states and observations occur in continuous time. Two different settings are
analyzed: hidden jump process with a finite state space, and hidden diffusion
process with a continuous state space. For each setting, we first estimate the
hidden states given the observations and model parameters, showing that the
posterior distribution of the hidden states can be described by differential
equations in continuous time. We then consider the estimation of unknown model
parameters, deriving the continuous-time formulas for the
expectation-maximization algorithm. We also propose a Monte Carlo method based
on the continuous formulation, sampling the posterior distribution of the
hidden states and updating the parameter estimation.

26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
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The categories of this paper are: q-alg
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The categories of this paper are: nucl-ex
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys