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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