set.seed(12)
indata <- createDataPartition(
  data$FSDI,
  p =.20,
  list = FALSE
)

training <- data[indata,]
testing <- data[-indata,]
set.seed(1)
brt1 <- gbm.step(data=data, gbm.x =5:13, gbm.y = 3,
                 family = "gaussian", tree.complexity = 5,
                 learning.rate = 0.01, bag.fraction = 0.8)
ggInfluence(brt1)
ggPD(brt1, rug = T)


brt1.prerun<- plot.gbm.4list(brt1)
brt1.boot <- gbm.bootstrap.functions(brt1, list.predictors=brt1.prerun, n.reps=5)


result <- ggPD_boot(brt1, list.4.preds=brt1.prerun, cex.line =1.2,
                    booted.preds=brt1.boot$function.preds, type.ci = "ribbon", ncol = 3, nrow = 3,
                    rug = T, rug.pos = "b", smooth= F, col.line = "#3282BD",
                    y.label = "SSI")

result