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=sys.frame(sys.parent()), weights=1, cens=0, base=0,
subset, geth=FALSE, ..., lfproc=locfit.raw)
formula |
Model Formula; e.g. |
data |
Data Frame. |
weights |
Prior weights (or sample sizes) for individual observations. This is typically used where observations have unequal variance. |
cens |
Censoring indicator. |
base |
Baseline for local fitting. For local regression models, specifying
a |
subset |
Subset observations in the data frame. |
geth |
Don't use. |
... |
Other arguments to |
lfproc |
A processing function to compute the local fit. Default is
|
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.
locfit.raw
# fit and plot a univariate local regression
data(ethanol, package="locfit")
fit <- locfit(NOx ~ E, data=ethanol)
plot(fit, get.data=TRUE)
# a bivariate local regression with smaller smoothing parameter
fit <- locfit(NOx~lp(E,C,nn=0.5,scale=0), data=ethanol)
plot(fit)
# density estimation
data(geyser, package="locfit")
fit <- locfit( ~ lp(geyser, nn=0.1, h=0.8))
plot(fit,get.data=TRUE)
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