View source: R/binary_segmentation.R
Takes a segment of the data and dispatches the choosen method
to the different optimizers.
1 2 | FindBestSplit(x, start, end, delta, n_obs, control, SegmentLossFUN,
optimizer = c("line_search", "section_search"))
|
x |
A n times p matrix or data frame. |
start |
The start index of the given segment |
end |
The end index of the given segment |
delta |
Numeric value between 0 and 0.5. This tuning parameter determines the minimal segment size proportional to the size of the dataset and hence an upper bound for the number of changepoints (roughly 1/δ). |
n_obs |
The number of observations in the data set. |
control |
A list with parameters that is accessed by the selected optimizer:
|
SegmentLossFUN |
A loss function as created by closure |
optimizer |
Which search technique should be used for performing individual splits in the binary segmentation alogrithm? Possible choices are
|
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