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 DataPairComp

Constraint 
Kind of constraint on Bradley's scores. If Constraint=0 , the sum of Bradley's scores should be equal to 1.
For other values for Constraint , the product of Bradley's scores should be equal to 1.(default constraint=0 )

Tcla 
Number of classes, default=1, no segmentation.

eps 
value of the convergence criteria for the EM algorithm (default eps=1e04 ).

eps1 
value of the criteria convergence for Dykstra algorithm (default eps1=1e04 ).

TestPi 
if TestPi=TRUE multiple comparison tests for Bradley's scores are performed. Else no multiple comparison test. (default is TestPi=TRUE )

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 
matrix describing the evolution of log likelihood at the different steps of the maximization procedure.

Lvr 
Final value of the log likelihood

Lambda 
numeric Final estimates of classes' weight

Pi 
list of Tcla elements containing Bradley'scores for the different criteria

Zh 
matrix of the belongings probabilities of the individuals to the different classes and the belonging class according to these probabilities

IC 
value of Information Criterion (AIC,BIC,CAIC)

Restestglob 
(given if TestPi=TRUE )
list of five elements:
lvrH0 matrix of size (Tcla * number of criteria), giving the value of the log likelihood under the hypothesis of equality of Bradley's scores
lvrH1 matrix of size (Tcla * number of criteria), giving the value of the log likelihood under the hypothesis of non equality of Bradley's scores
lRatio matrix of size (Tcla * number of criteria), giving the value of the log likelihood Ratio statistic
Pvalue matrix of size (Tcla * number of criteria), giving the P value of the log likelihood Ratio test
H1 matrix of size (Tcla * number of criteria) giving the result of rejection of equality of Bradley's scores

Restestprod 
(given if TestPi=TRUE and if Bradley's scores are not equal)
list of Tcla elements of type matrix of size (number of paired comparison * 7), each column corresponding to:
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 TestPi=TRUE )
list of Tcla elements containing Bradley'scores covariance matrices for the different criteria.

Examples
data(Cocktail)
show(Cocktail)
ResCock1<EstimBradley(Cocktail,Constraint=0,Tcla=1,eps=0.001,eps1=0.001,TestPi=TRUE)
show(ResCock1)
[Package
CompR version 1.0
Index]