• Corpus ID: 14656708

Forecasting with Unobserved Components Time Series Models

@inproceedings{Harvey2006ForecastingWU,
  title={Forecasting with Unobserved Components Time Series Models},
  author={Andrew Harvey},
  year={2006}
}
Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for `nowcasting'. The structural interpretation allows extensions to classes of models that are able to deal with various issues in multivariate series and to cope with non-Gaussian observations and nonlinear models. The statistical… 
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