| bs {splines} | R Documentation |
Generate the B-spline basis matrix for a polynomial spline.
bs(x, df = NULL, knots = NULL, degree = 3, intercept = FALSE, Boundary.knots = range(x))
x |
the predictor variable. Missing values are allowed. |
df |
degrees of freedom; one can specify df rather than
knots; bs() then chooses df-degree-1 knots at
suitable quantiles of x (which will ignore missing values). |
knots |
the internal breakpoints that define the
spline. 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. See also
Boundary.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. |
Boundary.knots |
boundary points at which to anchor the B-spline
basis (default the range of the data). If both knots and
Boundary.knots are supplied, the basis parameters do not
depend on x. Data can extend beyond Boundary.knots. |
A matrix of dimension length(x) * df, where either df
was supplied or if knots were supplied,
df = length(knots) + 3 + intercept. Attributes are returned
that correspond to the arguments to bs, and explicitly give
the knots, Boundary.knots etc for use by
predict.bs().
bs() 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.
Hastie, T. J. (1992) Generalized additive models. Chapter 7 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
ns, poly, smooth.spline,
predict.bs, SafePrediction
require(stats)
bs(women$height, df = 5)
summary(fm1 <- lm(weight ~ bs(height, df = 5), data = women))
## example of safe prediction
plot(women, xlab = "Height (in)", ylab = "Weight (lb)")
ht <- seq(57, 73, len = 200)
lines(ht, predict(fm1, data.frame(height=ht)))
## Consistency:
x <- c(1:3,5:6)
stopifnot(identical(bs(x), bs(x, df = 3)),
!is.null(kk <- attr(bs(x), "knots")),# not true till 1.5.1
length(kk) == 0)