lp {locfit} | R Documentation |
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 or adpen are
provided, in which case the default is 0.
|
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 (left ,
ang e.t.c.). Do not try to set this directly;
call locfit instead. |
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 ang terms. If scale=F (the default) no scaling
is performed. If scale=T , marginal standard deviations are used.
Alternatively, a numeric vector can provide scales for the
individual variables.
|
data(ethanol, package="locfit") # fit with 50 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))