An overview of modeling techniques for hybrid brain data
Statistica Sinica
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sg-nus-scholar.10635-1049992015-04-01T10:10:16Z An overview of modeling techniques for hybrid brain data Guha, A. Biswas, A. STATISTICS & APPLIED PROBABILITY AIC BIC Bivariate time series Continuous time series Hybrid process IMI Jump Markov linear gaussian system Markov model Maximum log-likelihood Point process Statistica Sinica 18 4 1311-1340 2014-10-28T05:10:02Z 2014-10-28T05:10:02Z 2008-10 Article Guha, A.,Biswas, A. (2008-10). An overview of modeling techniques for hybrid brain data. Statistica Sinica 18 (4) : 1311-1340. ScholarBank@NUS Repository. 10170405 http://scholarbank.nus.edu.sg/handle/10635/104999 NOT_IN_WOS Scopus |
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AIC BIC Bivariate time series Continuous time series Hybrid process IMI Jump Markov linear gaussian system Markov model Maximum log-likelihood Point process |
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AIC BIC Bivariate time series Continuous time series Hybrid process IMI Jump Markov linear gaussian system Markov model Maximum log-likelihood Point process Guha, A. Biswas, A. An overview of modeling techniques for hybrid brain data |
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Statistica Sinica |
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STATISTICS & APPLIED PROBABILITY |
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STATISTICS & APPLIED PROBABILITY Guha, A. Biswas, A. |
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Article |
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Guha, A. Biswas, A. |
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Guha, A. |
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An overview of modeling techniques for hybrid brain data |
title_short |
An overview of modeling techniques for hybrid brain data |
title_full |
An overview of modeling techniques for hybrid brain data |
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An overview of modeling techniques for hybrid brain data |
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An overview of modeling techniques for hybrid brain data |
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overview of modeling techniques for hybrid brain data |
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2014 |
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http://scholarbank.nus.edu.sg/handle/10635/104999 |
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