sol.idetect {breakfast} | R Documentation |
This function arranges all possible change-points in the mean of the input vector in the order of importance, via the Isolate-Detect (ID) method. It is developed to be used with the sdll and information criterion (ic) model selection rules.
sol.idetect(x, thr_ic = 0.9, points = 3)
x |
A numeric vector containing the data to be processed. |
thr_ic |
A positive real number with default value equal to 0.9. It is used to create the solution path. The lower the value, the larger the solution path vector. |
points |
A positive integer with default value equal to 3. It defines the distance between two consecutive end- or start-points of the right- or left-expanding intervals, as described in the Isolate-Detect methodology. |
The Isolate-Detect method and its algorithm is described in "Detecting multiple generalized change-points by isolating single ones", A. Anastasiou & P. Fryzlewicz (2021), Metrika, https://doi.org/10.1007/s00184-021-00821-6.
An S3 object of class cptpath
, which contains the following fields:
solutions.nested |
|
solution.path |
Locations of possible change-points in the mean of |
solution.set |
Empty list |
x |
Input vector |
cands |
Matrix of dimensions length( |
method |
The method used, which has value "idetect" here |
A. Anastasiou & P. Fryzlewicz (2021). Detecting multiple generalized change-points by isolating single ones. Metrika, https://doi.org/10.1007/s00184-021-00821-6.
sol.idetect_seq
, sol.not
, sol.wbs
, sol.wbs2
, sol.tguh
,
r3 <- rnorm(1000) + c(rep(0,300), rep(2,200), rep(-4,300), rep(0,200))
sol.idetect(r3)