Singular Autoregressions for Generalized Dynamic Factor Models
We consider Generalized Linear Dynamic Factor Models in a stationary context, where the latent variables and thus the static and dynamic factors are the sum of a linearly regular and a linearly singular stationary process and the noise process is linearly regular. The linearly singular component may be useful for modeling e.g. business cycles or seasonal fluctuations in the observed variables. We present a structure theory for this case. The emphasis is laid on the autoregressive case. In...[Show more]
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|Source:||IEEE Conference on Decision and Control 2010 Proceedings|
|01_Deistler_Singular_Autoregressions_for_2010.pdf||151.96 kB||Adobe PDF||Request a copy|
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