Description Objects from the Class Slots Methods Author(s) See Also Examples
A class for Bayesian Segmentation objects.
Objects can be created by calls of the form new("EBS", ...)
.
new("EBS", ...)
:creates a new object with class EBS
model
:Object of class "character"
, the assumed distribution of the data
data
:Object of class "numeric"
, the data to be segmented
length
:Object of class "numeric"
, the length of the profile
Kmax
:Object of class "numeric"
, the maximum number of segments considered for the segmentation
HyperParameters
:Object of class "numeric"
, the hyperparameters used for the prior distribution on the model parameters
Variance
:Object of class "numeric"
, if model = Normal Homoscedastic, the variance used in the analysis
overdispersion
:Object of class "numeric"
, if model = Negative Binomial, the overdispersion used in the analysis
Li
:Object of class "numeric"
, matrix of size Kmax*(length+1) where element [i,j] is the log-probability of interval [1,j[ being segmented in i segments
Col
:Object of class "numeric"
, a matrix of size (length+1)*Kmax where element [i,j] is the log-probability of interval [i,n] being segmented in j segments
matProba
:a matrix of size (length+1)*(length+1)where element [i,j] is the log-probability of interval [i,j[
unif
:a boolean stating whether prior on segmentation is uniform given number of segments
signature(object = "EBS")
: retrieves model slot
signature(object = "EBS")
: retrieves data slot
signature(object = "EBS")
: retrieves length slot
signature(object = "EBS")
: retrieves Kmax slot
signature(object = "EBS")
: retrieves HyperParameters slot
signature(object = "EBS")
: retrieves Variance slot
signature(object = "EBS")
: retrieves overdispersion slot
signature(object = "EBS")
: retrieves Li slot
signature(object = "EBS")
: retrieves Col slot
signature(object = "EBS")
: retrieves matProba slot
signature(object = "EBS")
: retrieves unif slot
Alice Cleynen
1 2 3 4 5 6 7 8 | showClass("EBS") # shows the structure of the cpt class
data<-c(rpois(100,2),rpois(100,5))
# creates a new EBS object containing the segmentation of x
E<-EBSegmentation(data)
class(E) # verifies the class of E
getModel(E) # retrieves model of the segmentation
getLength(E) # retrieves the length of the signal
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