locfit: smooth.lf – R documentation

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smooth.lf

Local Regression, Likelihood and Density Estimation.

Description

smooth.lf is a simple interface to the Locfit library. The input consists of a predictor vector (or matrix) and response. The output is a list with vectors of fitting points and fitted values. Most locfit.raw options are valid.

Usage

smooth.lf(x, y, xev=x, direct=FALSE, ...)

Arguments

`x`	Vector (or matrix) of the independent variable(s).
`y`	Response variable. If omitted, `x` is treated as the response and the predictor variable is `1:n`.
`xev`	Fitting Points. Default is the data vector `x`.
`direct`	Logical variable. If `T`, local regression is performed directly at each fitting point. If `F`, the standard Locfit method combining fitting and interpolation is used.
`...`	Other arguments to `locfit.raw()`.

Value

A list with components x (fitting points) and y (fitted values). Also has a call component, so update() will work.

Examples

# using smooth.lf() to fit a local likelihood model.
data(morths)
fit <- smooth.lf(morths$age, morths$deaths, weights=morths$n,
                 family="binomial")
plot(fit,type="l")

# update with the direct fit
fit1 <- update(fit, direct=TRUE)
lines(fit1,col=2)
print(max(abs(fit$y-fit1$y)))

locfit

Local Regression, Likelihood and Density Estimation

v1.5-9.4

GPL (>= 2)

Authors

Catherine Loader [aut], Jiayang Sun [ctb], Lucent Technologies [cph], Andy Liaw [cre]

Initial release

2020-03-24