Local Polynomial Model Term
lp is a local polynomial model term for Locfit models.
Usually, it will be the only term on the RHS of the model formula.
Smoothing parameters should be provided as arguments to lp(),
rather than to locfit().
lp(..., nn, h, adpen, deg, acri, scale, style)
... |
Predictor variables for the local regression model. |
nn |
Nearest neighbor component of the smoothing parameter.
Default value is 0.7, unless either |
h |
The constant component of the smoothing parameter. Default: 0. |
adpen |
Penalty parameter for adaptive fitting. |
deg |
Degree of polynomial to use. |
acri |
Criterion for adaptive bandwidth selection. |
style |
Style for special terms ( |
scale |
A scale to apply to each variable. This is especially important for
multivariate fitting, where variables may be measured in
non-comparable units. It is also used to specify the frequency
for |
data(ethanol, package="locfit") # fit with 50% nearest neighbor bandwidth. fit <- locfit(NOx~lp(E,nn=0.5),data=ethanol) # bivariate fit. fit <- locfit(NOx~lp(E,C,scale=TRUE),data=ethanol) # density estimation data(geyser, package="locfit") fit <- locfit.raw(lp(geyser,nn=0.1,h=0.8))
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