TY - JOUR
T1 - Discrete-time expectation maximization algorithms for Markov-modulated poisson processes
AU - Elliott, Robert J.
AU - Malcolm, W. P.
PY - 2008/1
Y1 - 2008/1
N2 - In this paper, we consider parameter estimation Markov-modulated Poisson processes via robust filtering and smoothing techniques. Using the expectation maximization algorithm framework, our filters and smoothers can be applied to estimate the parameters of our model in either an online configuration or an offline configuration. Further, our estimator dynamics do not involve stochastic integrals and our new formulas, in terms of time integrals, are easily discretized, and are written in numerically stable forms in W. P. Malcolm, R. J. Elliott, and J. van der Hoek, "On the numerical stability of time-discretlzed state estimation via dark transformations," presented at the IEEE Conf. Decision Control, Mauii, HI, Dec. 2003.
AB - In this paper, we consider parameter estimation Markov-modulated Poisson processes via robust filtering and smoothing techniques. Using the expectation maximization algorithm framework, our filters and smoothers can be applied to estimate the parameters of our model in either an online configuration or an offline configuration. Further, our estimator dynamics do not involve stochastic integrals and our new formulas, in terms of time integrals, are easily discretized, and are written in numerically stable forms in W. P. Malcolm, R. J. Elliott, and J. van der Hoek, "On the numerical stability of time-discretlzed state estimation via dark transformations," presented at the IEEE Conf. Decision Control, Mauii, HI, Dec. 2003.
KW - Change of measure
KW - Counting processes
KW - Expectation maximization (EM) algorithm
KW - Martingales
UR - http://www.scopus.com/inward/record.url?scp=78149237374&partnerID=8YFLogxK
U2 - 10.1109/TAC.2007.914305
DO - 10.1109/TAC.2007.914305
M3 - Article
SN - 0018-9286
VL - 53
SP - 247
EP - 256
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
IS - 1
ER -