infJack: The infinitesimal jackknife for random forests
In swager/randomForestCI: Confidence Intervals for Random Forests

The infinitesimal jackknife for random forests

1	infJack(pred, inbag, calibrate = TRUE, used.trees = NULL)

`pred`	A nrow(newdata) by no. of trees matrix which contains numeric predictions from a random forest trained with trees grown on bootstrap samples of the training data
`inbag`	A number of obs. in the training data by no. of trees matrix giving the number of times the ith observation in the training data appeared in the bootstrap sample for the jth tree.
`calibrate`	whether to apply calibration to mitigate Monte Carlo noise warning: if calibrate = FALSE, some variance estimates may be negative due to Monte Carlo effects if the number of trees in rf is too small
`used.trees`	set of trees to use for variance estimation; uses all tress if NULL