# 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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