next up previous
Next: Bibliography Up: Choice of parameters Previous: Window width

Parameters of the SSA algorithm: lag $M$ and group $I$

To choose values of the lag $M$ and the group $I$ of indices of the eigenvectors, we have to follow standard SSA recommendations. (For an extensive discussion of this problem we refer to Golyandina, Nekrutkin and Zhigljavsky (2001).) The separability characteristics (including the $\bf w$-correlation) play a very important role here. If $m$ is not very large, which should be regarded as the most interesting case in practice, we choose $M=m/2$ (recall that $m$ is assumed to be even) and $I=\{1,\ldots,l\}$, where $l$ is such that the first $l$ components describe well the signal and the lower $M-l$ components correspond to noise. To choose $l$, visual inspection of the SSA decomposition of the whole series and some large parts of the series before applying the change-point detection algorithms is advised. Alternatively, if the problem is really sequential and a preliminary study of the time series is not possible, then the recommendation is to use all the visual SSA tools in the first part of the series to choose $l$. If $l$ is too small (underfitting), then we miss a part of the signal and therefore we can miss a change (the change may occur in the underestimated components). Alternatively, if $l$ is too large (overfitting), then we approximate a part of noise together with the signal and therefore finding a change in signal becomes more difficult.
next up previous
Next: Bibliography Up: Choice of parameters Previous: Window width