EstimBradley {CompR}  R Documentation 
Estimation of Bradley's scores in the different classes of subjects
Description
Estimates Bradley's scores according the desired number of classes.
Usage
EstimBradley(Data, Constraint=0, Tcla=1, eps=1e04, eps1=1e04, TestPi=TRUE)
Arguments
Data 
Object of class 
Constraint 
Kind of constraint on Bradley's scores. If 
Tcla 
Number of classes, default=1, no segmentation. 
eps 
value of the convergence criteria for the EM algorithm (default 
eps1 
value of the criteria convergence for Dykstra algorithm (default 
TestPi 
if 
Details
The estimation is based on maximum likelihood for mixture distributions with E.M. algorithm.
Value
Object of class BradleyEstim
with the following components:
Lvriter 

Lvr 
Final value of the log likelihood 
Lambda 

Pi 

Zh 

IC 
value of Information Criterion (AIC,BIC,CAIC) 
Restestglob 
(given if

Restestprod 
(given if class identification, criterion identification, product identification i, product identification j, value for the statistic corresponding to H0: equality of the Bradley's scores of products i and j, P value of this test, Rejection or acceptation of H0 for a level of 5%. 
Varcov 
(given if

Examples
data(Cocktail)
show(Cocktail)
ResCock1<EstimBradley(Cocktail,Constraint=0,Tcla=1,eps=0.001,eps1=0.001,TestPi=TRUE)
show(ResCock1)