Confidence Intervals in Boosted Regression Trees

[Beatriz]

Hello,
I'm working with boosted regression trees and I'm trying to calculate confidence intervals using bootstrap sampling.
The script I'm using is the following:

fun=function(x){
  x=gbm.step(data=Dados, gbm.x = 2:21, gbm.y = 1,
             family = "gaussian", tree.complexity = 2,
             learning.rate = 0.001, bag.fraction = 0.5)
  y=plot.gbm(x,i.var = 9,return.grid = TRUE)
  return(y)
}

library(boot)
air.boot <- boot(Dados, fun, R = 2, sim = "parametric")

After runing this, the following error appears

Error in t.star[r, ] <- res[[r]] : 
  incorrect number of subscripts on matrix

I was hoping that the output of this script would be partial dependence plots already with confidence intervals or at least, a list of those values.
I apreciate every help, thank you in advance!

[Beatriz]

I read the description of the statistic argument of boot and I was confused, I thought it should create the same function as when running the gbm model normally.
However, each time these models run, the results are different, but I would like to be able to apply the boot function as it should be.

data.frame(stringsAsFactors=FALSE,
             Big = c(0, 0, 0.333333333333333, 0, 0.222222222222222),
      Tree_Cover = c("O", "MC", "SO", "SO", "SO"),
    Shrubs_Cover = c("SC", "SO", "MC", "MC", "MC"),
     Grass_Cover = c("O", "MC", "SO", "SO", "SO"),
      Naked_Soil = c(3, 3, 2, 4, 4),
     Tree_Height = c("L", "L", "L", "S", "L"),
   Shrubs_Height = c("T", "H", "H", "T", "H"),
    Grass_Height = c("L", "L", "L", "L", "L"),
         Class_1 = c(0.117021276595745, 0.0957446808510638, 0.448275862068966,
                     0.241379310344828, 0.174418604651163),
         Class_2 = c(1.27659574468085, 0.98936170212766, 0.436781609195402, 1,
                     0.930232558139535),
          ASPECT = c(249.43603515625, 180, 331.714447021484, 234.409713745117,
                     352.326171875),
             LST = c(35.2816772460938, 34.1432838439941, 33.1653289794922,
                     31.4487133026123, 32.2971000671387),
      STD_NDVI_B = c(0.01500074858112, 0.014454394578934, 0.011638629995286,
                     0.013905543973669, 0.019954839814454),
       SHANNON_B = c(0.689610832538761, 0.346549997727076, 0.692177726555679,
                     0.071274728544297, 0.425752818584442),
    TREE_COVER_B = c(18.25, 40.5384615384615, 40.28, 48.2, 37.36),
         SLOPE_B = c(4.79538814510618, 9.47576512893041, 14.4894498870486,
                     6.86611137219838, 17.1000535033998),
           DEM_B = c(37.5714285714286, 33.4761904761905, 46.6190476190476,
                     71.6666666666667, 73.7142857142857),
          NDVI_B = c(0.262836583350834, 0.307793959190971, 0.29465841149029,
                     0.25947109727483, 0.239990872889757),
              DB = c(84.9651798863, 91.8427150336, 94.7049892021,
                     96.0842022325, 8.1394943871),
              OB = c(13.466707799, 1.1228884385, 1.9836147833, 0.010425148,
                     11.9405545364),
               G = c(0.0018932598, 5.4682419431, 1.7454539994, 2.3386234488,
                     78.3532818967)
)