Time series smoothing by penalized least squares

The time series smoothing problem is approached in a slightly more general form than usual. The proposed statistical solution involves an implicit adjustment to the observations at both extremes of the time series. The resulting estimated trend becomes more statistically grounded and an estimate of its sampling variability is provided. An index of smoothness is derived and proposed as a tool for choosing the smoothing constant.