Hidden Markov Models with mixtures as emission distributions
被引:28
|
作者:
Volant, Stevenn
论文数: 0引用数: 0
h-index: 0
机构:
INRA, UMR MIA 518, F-75231 Paris, France
AgroParisTech, UMR MIA, F-75231 Paris, FranceINRA, UMR MIA 518, F-75231 Paris, France
Volant, Stevenn
[1
,2
]
Berard, Caroline
论文数: 0引用数: 0
h-index: 0
机构:
INRA, UMR MIA 518, F-75231 Paris, France
AgroParisTech, UMR MIA, F-75231 Paris, FranceINRA, UMR MIA 518, F-75231 Paris, France
Berard, Caroline
[1
,2
]
Martin-Magniette, Marie-Laure
论文数: 0引用数: 0
h-index: 0
机构:
INRA, UMR MIA 518, F-75231 Paris, France
AgroParisTech, UMR MIA, F-75231 Paris, France
INRA, URGV UMR1165, F-91057 Evry, France
UEVE, UMR URGV, F-91057 Evry, France
CNRS, UMR URGV ERL8196, F-91057 Evry, FranceINRA, UMR MIA 518, F-75231 Paris, France
Martin-Magniette, Marie-Laure
[1
,2
,3
,4
,5
]
Robin, Stephane
论文数: 0引用数: 0
h-index: 0
机构:
INRA, UMR MIA 518, F-75231 Paris, France
AgroParisTech, UMR MIA, F-75231 Paris, FranceINRA, UMR MIA 518, F-75231 Paris, France
In unsupervised classification, Hidden Markov Models (HMM) are used to account for a neighborhood structure between observations. The emission distributions are often supposed to belong to some parametric family. In this paper, a semiparametric model where the emission distributions are a mixture of parametric distributions is proposed to get a higher flexibility. We show that the standard EM algorithm can be adapted to infer the model parameters. For the initialization step, starting from a large number of components, a hierarchical method to combine them into the hidden states is proposed. Three likelihood-based criteria to select the components to be combined are discussed. To estimate the number of hidden states, BIC-like criteria are derived. A simulation study is carried out both to determine the best combination between the combining criteria and the model selection criteria and to evaluate the accuracy of classification. The proposed method is also illustrated using a biological dataset from the model plant Arabidopsis thaliana. A R package HMMmix is freely available on the CRAN.
机构:
Univ Paris Saclay, Lab Math Orsay, Univ Paris Sud, CNRS, F-91405 Orsay, FranceUniv Paris Saclay, Lab Math Orsay, Univ Paris Sud, CNRS, F-91405 Orsay, France
De Castro, Yohann
Gassiat, Elisabeth
论文数: 0引用数: 0
h-index: 0
机构:
Univ Paris Saclay, Lab Math Orsay, Univ Paris Sud, CNRS, F-91405 Orsay, FranceUniv Paris Saclay, Lab Math Orsay, Univ Paris Sud, CNRS, F-91405 Orsay, France
机构:Communications Research Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Taejon 305-701, 373-1, Kusung-dong, Yusung-gu
CHUNG, YJ
UN, CK
论文数: 0引用数: 0
h-index: 0
机构:Communications Research Laboratory, Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Taejon 305-701, 373-1, Kusung-dong, Yusung-gu