mosaic (version 1.8.3)

fitSpline: 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"),
  ...
)

Value

a function of the explanatory variable

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()).

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')