Description
Usage
Arguments
Value
Generate the Bspline basis matrix for a polynomial spline with derivative restrictions at the boundary knots.
 (x, = , = , degree = 3, intercept = ,
Boundary.knots = (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 (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 Bspline basis (default the range of the nonNA 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 .

A matrix with containing the basis functions evaluated in x
.
cuRe documentation built on April 23, 2020, 5:16 p.m.