Perform binning in order to remove missing values
A numeric matrix
Some segmentation methods (in particular, GFLars) do not
natively handle the situation when some observations have missing
values in one or more dimensions. In order to avoid dropping the
corresponding observations entirely,
the signal values of the last complete observation before a (range
of) observations with missing entries using the
In the specific case when the first row has NA values, the first non-missing entry is replicated in order to make smoothing possible. This choice is arbitrary but some arbitrary choice is needed in that case.
Currently this function is only used by
doGFLars in order to make it possible to run GFLars
segmentation on SNP array data where most markers (on the order of
2/3 to 5/6) have missing values, because of uninformative or
missing allelic ratio signals.
binMissingValues function may be used for other
segmentation methods suffering from the same limitation. However,
we emphasize that handling missing values natively in the
segmentation method would be a better solution.
Morgane Pierre-Jean and Pierre Neuvial
Bleakley, K., & Vert, J. P. (2011). The group fused lasso for multiple change-point detection. arXiv preprint arXiv:1106.4199.
Vert, J. P., & Bleakley, K. (2010). Fast detection of multiple change-points shared by many signals using group LARS. Advances in Neural Information Processing Systems, 23, 2343-2351.
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