| StatModel-class {modeltools} | R Documentation |
A class for unfitted statistical models.
Objects can be created by calls of the form new("StatModel", ...).
name:"character", the name of the
model.dpp:"function", a function for
data preprocessing (usually formula-based). fit:"function", a function for
fitting the model to data.predict:"function", a function for
computing predictions.capabilities:"StatModelCapabilities".signature(model = "StatModel", data = "ModelEnv"):
fit model to data.
This is an attempt to provide unified infra-structure for unfitted
statistical models. Basically, an unfitted model provides a function for
data pre-processing (dpp, think of generating design matrices),
a function for fitting the specified model to data (fit), and
a function for computing predictions (predict).
### linear model example df <- data.frame(x = runif(10), y = rnorm(10)) mf <- dpp(linearModel, y ~ x, data = df) mylm <- fit(linearModel, mf) ### the same print(mylm) lm(y ~ x, data = df) ### predictions Predict(mylm, newdata = data.frame(x = runif(10)))