Using tune with gbm --grid search for best hyperparameters

Hello LIST,

I'd like to use tune from e1071 to do a grid search for hyperparameter 
values in gbm. However, I can not get this to work. I note that there is no 
wrapper for gbm but that it is possible to use non-wrapped functions (like 
lm) without problem. Here's a snippet of code to illustrate.

data(mtcars) obj <- 
gbm(mpg~disp+wt+carb,data=mtcars,distribution="gaussian",n.trees=1000,n.minobsinnode=5) 
summary(obj) #just to demonstrate that gbm worked

var   rel.inf
1 disp 55.185469
2   wt 40.198605
3 carb  4.615926
# now let's find the best value for n.minobsinnode using tune

tune.obj <- 
tune(gbm,mpg~disp+wt+carb,data=mtcars,distribution="gaussian",n.trees=1000,n.minobsinnode=c(5,10,15))

Error in function (formula = formula(data), distribution = "bernoulli",  : 
  unused argument(s) (subset = c(23, 9, 18, 26, 32, 28, 16, 5, 25, 24, 21, 
8, 6, 7, 13, 1, 30, 17, 2, 29, 3, 27, 31, 12, 15, 11, 4, 22))

I've tried many variations on syntax --too many to count. But this error 
message will not go away. Does tune simply not work with gbm or is 
something else going on. Many thanks for any insight.

Christopher