R: Classic Backfitting

backf.cl {RBF} | R Documentation

## Classic Backfitting

### Description

This function computes the standard backfitting algorithm for additive models.

### Usage

    backf.cl(
      formula,
      data,
      subset,
      point = NULL,
      windows,
      epsilon = 1e-06,
      degree = 0,
      prob = NULL,
      max.it = 100
    )

### Arguments

`formula` | an object of class `formula` (or one that can be coerced to that class): a symbolic description of the model to be fitted.
`data` | an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in `data`, the variables are taken from `environment(formula)`, typically the environment from which the function was called.
`subset` | an optional vector specifying a subset of observations to be used in the fitting process.
`point` | matrix of points where predictions will be computed and returned.
`windows` | vector of bandwidths for the local polynomial smoother, one per explanatory variable.
`epsilon` | convergence criterion. Maximum allowed relative difference between consecutive estimates
`degree` | degree of the local polynomial smoother. Defaults to `0` (local constant).
`prob` | vector of probabilities of observing each response (length n). Defaults to `NULL` and in that case it is ignored.
`max.it` | Maximum number of iterations for the algorithm.

### Details

This function computes the standard backfitting algorithm for additive models, using a squared loss function and local polynomial smoothers.

### Value

A list with the following components:

`alpha` | Estimate for the intercept.
`g.matrix` | Matrix of estimated additive components (n by p).
`prediction` | Matrix of estimated additive components for the points listed in the argument `point`.

### Author(s)

Matias Salibian-Barrera, matias@stat.ubc.ca, Alejandra Martinez

### References

Hasie, TJ and Tibshirani, RJ. Generalized Additive Models, 1990. Chapman and Hall, London.

### Examples

    data(airquality)
    tmp <- backf.cl(Ozone ~ Solar.R + Wind + Temp, data=airquality,
    subset=complete.cases(airquality), windows=c(130, 9, 10), degree=1)

[Package RBF version 2.1.0 Index]