sol.tguh {breakfast} | R Documentation |
This function arranges all possible change-points in the mean of the input vector in the order of importance, via the Tail-Greedy Unbalanced Haar method.
sol.tguh(x, p = 0.01)
x |
A numeric vector containing the data to be processed |
p |
Specifies the number of region pairs merged
in each pass through the data, as the proportion of all remaining region pairs. The default is
|
The Tail-Greedy Unbalanced Haar decomposition algorithm is described in "Tail-greedy bottom-up data decompositions and fast multiple change-point detection", P. Fryzlewicz (2018), The Annals of Statistics, 46, 3390–3421.
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 |
M |
Input parameter |
cands |
Matrix of dimensions length( |
method |
The method used, which has value "tguh" here |
P. Fryzlewicz (2018). Tail-greedy bottom-up data decompositions and fast multiple change-point detection. The Annals of Statistics, 46, 3390–3421.
sol.idetect
, sol.idetect_seq
, sol.not
, sol.wbs
, sol.wbs2
r3 <- rnorm(1000) + c(rep(0,300), rep(2,200), rep(-4,300), rep(0,200))
sol.tguh(r3)