degrees of freedom; one can specify df rather than knots; bs then
chooses df-degree-1 knots at suitable quantiles of x.
knots:
the
internal
breakpoints that define the spline; the range of the data provide the boundary knots. The default is NULL, which results in a
basis for ordinary polynomial regression. Typical values
are the mean or median for one knot, quantiles for more knots.
degree:
degree of the piecewise polynomial---default is 3 for cubic splines.
intercept:
if TRUE, an intercept is included in the basis; default is FALSE.
VALUE:
a matrix of dimension length(x) * df, where either df was supplied or
if knots were supplied, df = length(knots) + 3 + intercept.
DETAILS:
The bs function is based on the function spline.des.
It generates a basis matrix for representing the family of
piecewise polynomials with the specified interior knots and degree,
evaluated at the values of x.
A primary use is in modeling formulas to directly specify
a piecewise polynomial term in a model.
REFERENCES:
de Boor, C. (1978).
A Practical Guide to Splines.
Berlin: Springer Verlag.
Cheney, W., Kincaid, D. (1985).
Numerical Mathematics and Computing, Second edition.
New York: Brooks/Cole Publishing Co.