plot.plfm | R Documentation |
plfm
objectPlot method to visualize the parameters of probabilistic feature models.
## S3 method for class 'plfm' plot(x,feature=1,element="object",cexsymb=1,cexlabel=1,...)
x |
Probabilistic feature model object returned by |
feature |
Latent feature for which parameters are visualized. |
element |
Object parameters are plotted if |
cexsymb |
Size of symbol used for plotting points. |
cexlabel |
Size of object- or attribute labels in plot. |
... |
Further arguments are ignored. |
# examples ## Not run: # example 1:Perceptual analysis of associations between car models and car attributes # load car data data(car) # compute 1 run of a disjunctive model with 4 features # use components of a data frame as input cardisj4<-plfm(datatype="dataframe",data=car$datalongformat,object=objectlabel, attribute=attributelabel,rating=rating,maprule="disj",F=4,M=1) # plot car and attribute parameters per feature par(mfrow=c(1,2)) plot(cardisj4,feature=1,element="object",main="Car parameters Feature 1") plot(cardisj4,feature=1,element="attribute",main="Attribute parameters Feature 1") par(mfrow=c(1,2)) plot(cardisj4,feature=2,element="object",main="Car parameters Feature 2") plot(cardisj4,feature=2,element="attribute",main="Attribute parameters Feature 2") par(mfrow=c(1,2)) plot(cardisj4,feature=3,element="object",main="Car parameters Feature 3") plot(cardisj4,feature=3,element="attribute",main="Attribute parameters Feature 3") par(mfrow=c(1,2)) plot(cardisj4,feature=4,element="object",main="Car parameters Feature 4") plot(cardisj4,feature=4,element="attribute",main="Attribute parameters Feature 4") ## End(Not run) par(mfrow=c(1,2)) # example 2: analysis on determinants of anger-related behavior # load anger data data(anger) # compute 1 run of a disjunctive model with 4 features # use frequency data as input angerdisj2<-plfm(maprule="disj",freq1=anger$freq1,freqtot=anger$freqtot,F=2,M=1) # plot situation and behavior parameters par(mfrow=c(2,2)) for (f in 1:2){ plot(angerdisj2,feature=f,element="object",main=paste("Situation parameters Feature",f,sep=" "))} for (f in 1:2){ plot(angerdisj2,feature=f,element="attribute",main=paste("Behavior parameters Feature",f,sep=" "))}
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