Currently available methods include:lm, glm, loess, step, ppr,
rpart[rpart], tree[tree],
randomForest[randomForest], mars[mda],
polymars[polspline], lars[lars], rq[quantreg],
lqs[MASS], rlm[MASS], svm[e1071], and nnet[nnet].
Additional methods wrappers can be created to allow for modelling
using custom functions. The only requirements are for a wrapper
function to be constructed taking parameters quantmod
,
training.data
, and .... The function must return the
fitted model object and have a predict method available.
It is possible to add predict methods if non exist by
adding an S3 method for predictModel. The buildModel.skeleton
function can be used for new methods.