View source: R/Functions_LpS.R
second.step.detect | R Documentation |
Backward elimination algorithm function for screening
second.step.detect(
data,
pts,
omega,
lambda,
mu,
alpha_L = 0.25,
verbose = FALSE
)
data |
a n by p dataset matrix |
pts |
a vector includes all candidate change points obtained by the first step |
omega |
tuning parameter for the information criterion function |
lambda |
tuning parameter for sparse component estimation |
mu |
tuning parameter for low rank component estimation |
alpha_L |
a numeric value, indicates the size of constraint space of low rank component |
verbose |
if TRUE, then it provides all information for current stage |
A list object includes
Final selected change points
Values of information criterion
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