TY - JOUR
T1 - Likelihood computation for hidden Markov models via generalized two-filter smoothing
AU - Persing, Adam
AU - Jasra, Ajay
N1 - Generated from Scopus record by KAUST IRTS on 2019-11-20
PY - 2013/5/1
Y1 - 2013/5/1
N2 - We introduce an estimate for the likelihood of hidden Markov models (HMMs) using sequential Monte Carlo (SMC) approximations of the generalized two-filter smoothing decomposition (Briers etal., 2010). This estimate is unbiased and a central limit theorem (CLT) is established. The new estimate is also investigated from a numerical perspective. © 2013 Elsevier B.V.
AB - We introduce an estimate for the likelihood of hidden Markov models (HMMs) using sequential Monte Carlo (SMC) approximations of the generalized two-filter smoothing decomposition (Briers etal., 2010). This estimate is unbiased and a central limit theorem (CLT) is established. The new estimate is also investigated from a numerical perspective. © 2013 Elsevier B.V.
UR - https://linkinghub.elsevier.com/retrieve/pii/S0167715213000485
UR - http://www.scopus.com/inward/record.url?scp=84874682709&partnerID=8YFLogxK
U2 - 10.1016/j.spl.2013.02.005
DO - 10.1016/j.spl.2013.02.005
M3 - Article
SN - 0167-7152
VL - 83
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
IS - 5
ER -