R: Classic Backfitting

backf.cl {RBF}

R Documentation

Classic Backfitting

This function computes the standard backfitting algorithm for additive models.

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

`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.

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

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`.

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

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

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 2.0.1 Index]