Description Usage Arguments Value Author(s) References
First generating the panel of statistics via wavelet-based filtering of the estimated common components, it applies the Double CUSUM Binary Segmentation in combination with the bootstrap generated thresholds to estimate the multiple change-points in the common components.
1 2 |
gfm |
a |
q |
the number of factors |
scales |
see |
sig.lev |
see |
rule |
the height of a binary tree for change-point analysis, see the Appendix of Barigozzi, Cho & Fryzlewicz (2016) |
B |
the size of bootstrap samples |
p |
see |
dw |
see |
mby |
see |
tby |
see |
do.parallel |
see |
tree |
a list containing the binary tree grown for change-point analysis on the common components; each node contains its index, the start and end of the segment as well as the estimated change-point, the test statistic and the proportion of bootstrap statistics smaller than the test statistic. |
est.cps |
a vector of change-points estimated for the common components; adjusted for the bias introduced by the wavelet filtering |
p.seq |
a sequence of the reciprocals of the average block size selected for the factors |
Haeran Cho
M. Barigozzi, H. Cho and P. Fryzlewicz (2016) Simultaneous multiple change-point and factor analysis for high-dimensional time series, Preprint.
H. Cho (2016) Change-point detection in panel data via double CUSUM statistic. Electronic Journal of Statistics. 10: 2000-2038.
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