Abstract
The package provides multivariate time series models for structural analysis, allowing one to extract latent signals such as trends or seasonality. Models are fitted using maximum likelihood estimation, allowing for non-stationarity, fixed regression effects, and ragged-edge missing values. Simple types of extreme values can be corrected using the device of entropy maximization. Model adequacy is assessed through residual diagnostics, and model-based signal extraction filters can be assessed in time domain and frequency domain. Extracted signals are produced with uncertainty measures that account for sample edge effects and missing values, and the signals (as well as the original time series) can be forecasted.
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