bsx {cuRe} | R Documentation |
Polynomial B-splines with eXtensions
Description
Generate the B-spline basis matrix for a polynomial spline with derivative restrictions at the boundary knots.
Usage
bsx(
x,
df = NULL,
knots = NULL,
degree = 3,
intercept = FALSE,
Boundary.knots = range(x),
deriv = NULL
)
Arguments
x |
the predictor variable. Missing values are allowed.
|
df |
degrees of freedom; one can specify df rather than knots; bs() then chooses
df -degree (minus one if there is an intercept) knots at suitable quantiles of x
(which will ignore missing values). The default, NULL , corresponds to no inner knots,
i.e., degree -intercept .
|
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 non-NA data).
If both knots and Boundary.knots are supplied, the basis parameters do not depend on x .
Data can extend beyond Boundary.knots .
|
deriv |
an integer vector of length 2 with values between 0 and degree + 1 giving the
derivative constraint order at the left and right boundary knots;
an order of 2 constrains the second derivative to zero (f”(x)=0);
an order of 1 constrains the first and second derivatives to zero (f'(x)=f”(x)=0);
an order of 0 constrains the zero, first and second derivatives to zero (f(x)=f'(x)=f”(x)=0)
An order of degree + 1 computes the basis matrix similarly to bs .
|
Value
A matrix with containing the basis functions evaluated in x
.
[Package
cuRe version 1.1.1
Index]