I have a question regarding the use of the dlm CRAN package for forecasting values of a seasonal time series.
I've built a dlm model combining a stochastic local level model with a stochastic trigonometric (Fourier representation) seasonal component of period 96 (measurements every 15 mins with a daily cycle).
I used dlmMLE to estimate the parameters for my data and filtered and smoothed the series which all seems to be working fine.
However, when I try to use the dlmForecast function to predict out-of-sample observations, the predictions stay constant. The value of all "predictions" are equal to the sum of the filtered level and filtered seasonal components for the final observation in the series.
I have used dlmForecast with several other models including a model with a seasonal factor component but never before with a trigonometric seasonal component.
I notice in the documentation for dlmForecast it says "Currently, only constant models are allowed" so I wonder if this applies to trigonometric seasonal models.