We propose a simple procedure for evaluating the marginal likelihood in univariate Structural Time Series (STS) models. For this we exploit the statistical properties of STS models and the results in Dickey (1968) to obtain the likelihood function marginally to the variance parameters. This...

We analyze the situation in which the decomposition of a time series into orthogonal balanced components as performed by the AR IMA-model-based (AMB) method is nonadmissible. We show that considering top-heavy models for the components can solve the problem. The top-heavy decomposition is...

We deal with the problem of decomposing a time series into the sum of unobserved components as in detrending or seasonal adjustment. In particular, we analyze the situation in which the decomposition into orthogonal balanced components as performed by the ARIMA-Model-Based method is...