Last data update: 2014.03.03
|
R: Fit splines to data
Fit splines to data
Description
These functions create mathematical functions from data, using splines.
Usage
fitSpline(formula, data = parent.frame(), df = NULL, knots = NULL,
degree = 3, type = c("natural", "linear", "cubic", "polynomial"), ...)
Arguments
formula |
a formula. Only one quantity is allowed on the left-hand side, the
output quantity
|
data |
a data frame in which formula is evaluated.
|
df |
degrees of freedom (used to determine how many knots should be used)
|
knots |
a vector of knots
|
degree |
parameter for splines when type is "polynomial" .
1 is locally linear, 2 is locally quadratic, etc.
|
type |
type of splines to use; one of
"linear" , "cubic" , "natural" (cubic with linear tails, the default),
or "polynomial" .
|
... |
additional arguments passed to spline basis functions
(ns and bs ).
|
Value
a function of the explanatory variable
See Also
bs and ns for the bases used to generate the splines.
Examples
f <- fitSpline( weight ~ height, data=women, df=5 )
xyplot( weight ~ height, data=women )
plotFun(f(height) ~ height, add=TRUE)
g <- fitSpline( length ~ width, data = KidsFeet, type='natural', df=5 )
h <- fitSpline( length ~ width, data = KidsFeet, type='linear', df=5 )
xyplot( length ~ width, data = KidsFeet, col='gray70', pch=16)
plotFun(g, add=TRUE, col='navy')
plotFun(h, add=TRUE, col='red')
Results
|