Maximum likelihood estimation in discrete mixed hidden Markov models using the SAEM algorithm

Computational Statistics and Data Analysis

Volumn 56, Issue 6, 2012, Pages 2073-2085

  Delattre, M ^a   Lavielle, M ^a  

^a INRIA SACLAY   (France)

Author keywords

Epileptic seizures count; Forward backward algorithm; Nonlinear mixed effects model; SAEM algorithm

Indexed keywords

BAUM-WELCH ALGORITHMS; CLINICAL TRIAL; EM ALGORITHMS; EPILEPTIC PATIENTS; EPILEPTIC SEIZURES; FORWARD BACKWARD ALGORITHMS; HIDDEN STATE; HIGHLY NONLINEAR; INFERENCE ALGORITHM; LONGITUDINAL DATA; MONTE CARLO SIMULATION; NONLINEAR MIXED EFFECTS; RANDOM EFFECTS; SAEM ALGORITHM; STOCHASTIC APPROXIMATIONS;

ALGORITHMS; APPROXIMATION THEORY; GRAPHICAL USER INTERFACES; HIDDEN MARKOV MODELS; INFERENCE ENGINES; INTELLIGENT SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION;

PARAMETER ESTIMATION;

EID: 84857657154     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2011.12.017     Document Type: Article

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