sol.tguh {breakfast}  R Documentation 
This function arranges all possible changepoints in the mean of the input vector in the order of importance, via the TailGreedy 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 TailGreedy Unbalanced Haar decomposition algorithm is described in "Tailgreedy bottomup data decompositions and fast multiple changepoint 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 changepoints 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). Tailgreedy bottomup data decompositions and fast multiple changepoint 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)