locfit Local Regression, Likelihood and Density Estimation. locfit

## Usage:

locfit(formula, data, weights, cens, base, subset, geth, ..., lfproc)

## Description:

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.

## Arguments:

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().

## Value:

An object with class "locfit". A standard set of methods for printing, ploting, etc. these objects is provided.

locfit.raw

## Examples:

```
# fit and plot a univariate local regression
data(ethanol)
fit <- locfit(NOx~E,data=ethanol)
plot(fit,get.data=T)

# 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)
fit <- locfit(~geyser, alpha=c(0.1,0.8))
plot(fit,get.data=T)
```

## References:

Loader, C. (1999). Local Regression and Likelihood. Springer, New York.

## Key Words:

smooth
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