cpt.range-class {changepoint} | R Documentation |
Class "cpt.range"
Description
A class for changepoint objects that return more than 1 segmentation. Inherits from cpt class.
Objects from the Class
Objects can be created by calls of the form new("cpt.range", ...)
.
new("cpt.range", ...)
:creates a new object with class cpt.range
Slots
cpts.full
:Object of class
"matrix"
, each row of the matrix is a different segmentation of the data (different set of changepoints).pen.value.full
:Object of class
"vector"
, each element is the penalty used to create the set of changepoints in the corresponding row ofcpts.full
.
The remaining slots are inherited from the cpt
class.
data.set
:Object of class
"ts"
, a coerced time series of the original data. Inherited from cpt class.cpttype
:Object of class
"character"
, the type of changepoint that was identified. Inherited from cpt class.method
:Object of class
"character"
, the method that was used to search for changepoints. Inherited from cpt class.test.stat
:Object of class
"character"
, the test statistic for the analysis of the data. Inherited from cpt class.pen.type
:Object of class
"character"
, the penalty type specified in the analysis. Inherited from cpt class.pen.value
:Object of class
"numeric"
, the value of the penalty used in the analysis. Inherited from cpt class.minseglen
:Object of class
"numeric"
, the minimum segment length (no. of observations between changepoints) used in the analysis. Inherited from cpt class.cpts
:Object of class
"numeric"
, vector of optimal changepoints identified. Inherited from cpt class.ncpts.max
:Object of class
"numeric"
, maximum number of changepoint that can be identified. Inherited from cpt class.param.est
:Object of class
"list"
, list where each element is a vector of parameter estimates, if requested. Inherited from cpt class.date
:Object of class
"character"
, date and time the changepoint analysis was run. Inherited from cpt class.version
:Object of class
"character"
, version number of the package used when the analysis was run. Inherited from cpt class.
Methods
- cpts.full
signature(object = "cpt.range")
: retrieves cpts.full slot- pen.value.full
signature(object = "cpt.range")
: retrieves pen.value.full slot- cpts.full<-
signature(object = "cpt.range")
: replaces cpts.full slot- param
signature(object="cpt.range",ncpts=NA)
: creates parameter estimates for the segmentation withncpts
number of changepoints. If ncpts=NA then the optimal set of changepoints according to the set penalty is used.- pen.value.full<-
signature(object = "cpt.range")
: replaces pen.value.full slot- plot
signature(object="cpt.range",ncpts=NA,diagnostic=FALSE)
: by default plots the optimal segmentation as forclass="cpt"
. If ncpts is specified then plots the segmentation forncpts
number of changepoints. Ifdiagnostic=TRUE
then produces a diagnostic plot to aide selection of the number of changes.signature(object = "cpt.range")
: prints details of the cpt.range object including summary- summary
signature(object = "cpt.range")
: prints a summary of the cpt.range object
Author(s)
Rebecca Killick
See Also
cpts.full-methods
,cpt
,cpt.mean
,cpt.var
,cpt.meanvar
Examples
showClass("cpt.range") # shows the structure of the cpt.range class
x=new("cpt.range") # creates a new object with the cpt.range class defaults
cpts(x) # retrieves the cpts slot from x
cpts(x)<-c(10,50,100) # replaces the cpts slot from x with c(10,50,100)
# Example of multiple changes in variance at 50,100,150 in simulated normal data
set.seed(1)
x=c(rnorm(50,0,1),rnorm(50,0,10),rnorm(50,0,5),rnorm(50,0,1))
out=cpt.var(x,pen.value=c(log(length(x)),10*log(length(x))),penalty="CROPS",method="PELT")
print(out) # prints details of the analysis including a summary
summary(out)
plot(out,diagnostic=TRUE) # a diagnostic plot to identify number of changepoints
# looks like the segmentation with 3 changepoints, 50,99,150 is the most appropriate
plot(out,ncpts=3) # plots the segmentation for 3 changes
logLik(out,ncpts=3)
# raw likelihood of the data with changepoints, second value is likelihood + penalty