Partial Correlation Graphs and Dynamic Latent Variables for Physiological Time Series
نویسندگان
چکیده
Latent variable techniques are helpful to reduce high-dimensional time series to a few relevant variables that are easier to model and analyze. An inherent problem is the identifiability of the model and the interpretation of the latent variables. We apply graphical models to find the essential relations in the data and to deduce suitable assumptions leading to meaningful latent variables.
منابع مشابه
Latent variable analysis and partial correlation graphs for multivariate time series
OO F Latent variable analysis and partial correlation graphs for multivariate time series Roland Fried , Vanessa Didelez Departamento de Estadı́stica, Universidad Carlos III de Madrid, 28903 Getafe, Spain University College London, London WC1E 6BT, UK Received 14 January 2003 R CT ED P Abstract We investigate the possibility of exploiting partial correlation graphs for identifying interpretable ...
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