model.thresh {breakfast} | R Documentation |
Estimating change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via thresholding
Description
This function estimates the number and locations of change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via thresholding.
Usage
model.thresh(cptpath.object, sigma = NULL, th.const = NULL)
Arguments
cptpath.object |
A solution-path object, returned by a |
sigma |
An estimate of the standard deviation of the noise in the data |
th.const |
A positive real number used to define the threshold for the detection process. The default used in the piecewise-constant model is 1.15, while in the piecewise-linear model, the value is taken equal to 1.4. |
Value
An S3 object of class cptmodel
, which contains the following fields:
solution.path |
The solution path method used to obtain |
type |
The model type used, inherited from the given |
model.selection |
The model selection method used to return the final change-point estimators object, here its value is |
no.of.cpt |
The number of estimated change-points |
cpts |
The locations of estimated change-points |
est |
An estimate of the mean of the vector |
See Also
sol.idetect
, sol.idetect_seq
, sol.not
, sol.tguh
, sol.wbs
, sol.wbs2
, breakfast
Examples
f <- rep(rep(c(0, 1), each = 50), 10)
x <- f + rnorm(length(f))
model.thresh(sol.idetect_seq(x))