Random Forest (rfsrc package) Multivar analysis

I'm trying to evaluate interactions between promotions on child products. My dataset counts 1073 dicotomic variables (x) and 11 dependent (y). I'm using rfsrc package in R.

Code: fit2=rfsrc(Multivar(y1,y2,y3,y4,y5,y6,y7,y8,y9,y10,y11) ~.,data = data3, importance =TRUE) err <- get.mv.error(fit2) err vmp.std <- get.mv.vimp(fit2, standardize = TRUE) plot(fit2)

Why, by default, R give me back just y1 as response?

Sample size: 602 Number of trees: 1000 Forest terminal node size: 5 Average no. of terminal nodes: 179.484 No. of variables tried at each split: 358 Total no. of variables: 1073 Total no. of responses: 11 User has requested response: y1 Resampling used to grow trees: swr Resample size used to grow trees: 602 Analysis: mRF-R Family: regr+ Splitting rule: mv.mse random Number of random split points: 10 % variance explained: 53.03 Error rate: 0.4 There are some command to plot some informations? Thanks in advance and sorry for my english. Cheers, Alessandro