See `?regr.randomForest` for information about se estimation. Note that the rf can freeze the R process if trained on a task with 1 feature which is constant. This can happen in feature forward selection, also due to resampling, and you need to remove such features with removeConstantFeatures. keep.inbag is NULL by default but if predict.type = 'se' and se.method = 'jackknife' (the default) then it is automatically set to TRUE.

Argument of: randomForest::randomForest

Number of trees to grow.  This should not be set to too small a number, to ensure that every input row gets predicted at least a few times.

Argument of: randomForest::randomForest

Number of variables randomly sampled as candidates at each split.  Note that the default values are different for classification (sqrt(p) where p is number of variables in x) and regression (p/3)

Argument of: randomForest::randomForest

Should sampling of cases be done with or without replacement?

Argument of: randomForest::randomForest

A (factor) variable that is used for stratified sampling.

Argument of: randomForest::randomForest

Size(s) of sample to draw.  For classification, if sampsize is a vector of the length the number of strata, then sampling is stratified by strata, and the elements of sampsize indicate the numbers to be drawn from the strata.

Argument of: randomForest::randomForest

Minimum size of terminal nodes.  Setting this number larger causes smaller trees to be grown (and thus take less time). Note that the default values are different for classification (1) and regression (5).

Argument of: randomForest::randomForest

Maximum number of terminal nodes trees in the forest can have.  If not given, trees are grown to the maximum possible (subject to limits by nodesize).  If set larger than maximum possible, a warning is issued.

Argument of: randomForest::randomForest

Should importance of predictors be assessed?

Argument of: randomForest::randomForest

Should casewise importance measure be computed? (Setting this to TRUE will override importance.)