Wrapper for Several Model Functions

Popular implementations of algorithms are characterized by partly unconventional implementations of the operating standards in R. For example, the function e1071::SVM() returns the predicted values as attributes!
FitMod() is designed as a wrapping function to offer a consistent interface for a selection of most often used classification and regression models.

Usage

FitMod(formula, data, ..., subset, na.action = na.pass, fitfn = NULL)

# S3 method for class 'FitMod'
predict(object, ...)
# S3 method for class 'FitMod'
plot(x, ...)
# S3 method for class 'FitMod'
summary(object, ...)
# S3 method for class 'FitMod'
drop1(object, ...)

Arguments

x: a fitted object of class "FitMod".
formula: a formula expression as for classification and regression models, of the form response ~ predictors. The response should be a factor or a matrix with K columns, which will be interpreted as counts for each of K classes. See the documentation of formula() for other details.
data: an optional data frame in which to interpret the variables occurring in formula.
subset: expression saying which subset of the rows of the data should be used in the fit. All observations are included by default.
na.action: a function to filter missing data.
fitfn: code for the fitting function to be used for regression or classifying. So far implemented are: lm, lmrob, poisson, quasipoisson, gamma, negbin, poisson, polr, tobit, zeroinfl, multinom, poisson, rpart, randomForest, logit, nnet, C5.0, lda, qda, svm, naive_bayes, lb.
object: the model object.
...: further arguments passed to the underlying functions.

Details

The function will in general return the original object, extended by a further class FitMod, which allows to capture the output and plot routines.

The classifying algorithms will at the minimum offer the predicting options type = c("class", "prob") additionally to those implemented by the underlying function.

Value

model object as returned by the calculating function extended with the FitMod class.

Author

Andri Signorell <andri@signorell.net>

Examples

r.lm <- FitMod(Fertility ~ ., data=swiss, fitfn="lm")

r.logit <- FitMod(diabetes ~ glucose + pressure + mass + age,
                  data=d.pima, fitfn="logit")
r.svm <- FitMod(diabetes ~ glucose + pressure + mass + age,
                  data=d.pima, fitfn="svm")