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assess the fit of the model using ROC curves and auc values
GOFaplsm(model, type, Y.i, Y.ia)
object of class the APLSM
character indicating the types of model. It could be "DD", distance by distance model, "DV", distance by vector model, "VV", vector by vector model
N by N matrix containing the binary social network
N by M matrix containing the binary multivariate attributes
list containing:
Yi.auc scaler of the area under the curve for the social network
Yi.auc
Ya.auc scaler of the area under the curve for the multivariate covariates
Ya.auc
# NOT RUN { attach(french) b=aplsm(Niter=3,Y.i, Y.ia,D=2, type="DD") GOFaplsm(b, "DD",Y.i, Y.ia) # }
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