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=1e-04, eps1=1e-04, 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)