Highlevel function for multivariate fused Lars (GFLars) segmentation
1 
Y 
A 
K 
The number of change points to find 
stat 
A vector containing the names or indices of the columns of 
... 
Further arguments to be passed to 'segmentByGFLars' 
verbose 
A 
This function is a wrapper around the lowerlevel
segmentation function segmentByGFLars
. It can be run
on pdimensional, piecewiseconstant data in order to defined a
set of candidate change points. It is recommended to prune this
list of candidates using dynamic programming
(pruneByDP
), combined with a selection of the best
number of change points. The jointSeg
function
provides a convenient wrapper for performing segmentation, pruning
and model selection.
For the specific case of DNA copy number data segmentation, see the
dedicated wrapper PSSeg
.
The default weights √{n/(i*(ni))} are calibrated as suggested by Bleakley and Vert (2011). Using this calibration, the first breakpoint maximizes the likelihood ratio test (LRT) statistic.
An object of the same structure as the output of segmentByGFLars
This implementation is derived from the MATLAB code by Vert and Bleakley: http://cbio.ensmp.fr/GFLseg.
Morgane PierreJean and Pierre Neuvial
Bleakley, K., & Vert, J. P. (2011). The group fused lasso for multiple changepoint detection. arXiv preprint arXiv:1106.4199.
Vert, J. P., & Bleakley, K. (2010). Fast detection of multiple changepoints shared by many signals using group LARS. Advances in Neural Information Processing Systems, 23, 23432351.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  p < 2
trueK < 10
sim < randomProfile(1e4, trueK, 1, p)
Y < sim$profile
K < 2*trueK
res < doGFLars(Y, K)
print(res$bkp)
print(sim$bkp)
plotSeg(Y, res$bkp)
## a toy example with missing values
sim < randomProfile(1e2, 1, 0.1, 2)
Y < sim$profile
Y[3:50, 2] < NA
res < doGFLars(Y, 10, 2, verbose=TRUE)
print(res$bkp)
print(sim$bkp)
plotSeg(Y, res$bkp)

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