locfit {locfit} | R Documentation |
locfit
is the model formula-based interface to the Locfit
library for fitting local regression and likelihood models.
locfit
is implemented as a front-end to locfit.raw
.
See that function for options to control smoothing parameters,
fitting family and other aspects of the fit.
locfit(formula, data, weights, cens, base, subset, geth, ..., lfproc)
formula |
Model Formula; e.g. y~x for a regression model; ~x for a
density estimation model
|
data |
Data Frame. |
weights |
Prior weights (or sample sizes) for individual observations. This is typically used where observations have unequal variance. |
cens |
Censoring indicator. 1 (or TRUE ) denotes a censored observation.
0 (or FALSE ) denotes uncensored.
|
base |
Baseline for local fitting. For local regression models, specifying
a base is equivalent to using y-base as the reponse. But base
also works for local likelihood.
|
subset |
Subset observations in the data frame. |
geth |
Don't use. |
... |
Other arguments to locfit.raw() (or the lfproc ).
|
lfproc |
A processing function to compute the local fit. Default is
locfit.raw() . Other choices include locfit.robust() ,
locfit.censor() and locfit.quasi() .
|
An object with class "locfit"
. A standard set of methods for printing,
ploting, etc. these objects is provided.
Loader, C. (1999). Local Regression and Likelihood. Springer, New York.
# fit and plot a univariate local regression data(ethanol) fit <- locfit(NOx~E,data=ethanol) plot(fit,get.data=TRUE) # a bivariate local regression with smaller smoothing parameter fit <- locfit(NOx~E+C, data=ethanol, scale=0, alpha=0.5) plot(fit) # density estimation data(geyser, package="locfit") fit <- locfit(~geyser, alpha=c(0.1,0.8)) plot(fit,get.data=TRUE)