This function produces the derivative of given order of B-splines. It is an implementation of the close form derivative of B-spline basis based on recursion relation. At knots, the derivative is defined to be the right derivative.

dbs(x, derivs = 1L, df = NULL, knots = NULL, degree = 3L,
    intercept = FALSE, Boundary.knots = range(x, na.rm = TRUE), ...)



The predictor variable. Missing values are allowed and will be kept and returned as they were.


A positive integer specifying the order of derivative. By default, it is 1L for the first derivative.


Degrees of freedom of the B-spline basis to be differentiated. One can specify df rather than knots, then the function 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".


The internal breakpoints that define the B-spline basis to be differentiated. 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.


Non-negative integer degree of the piecewise polynomial to be differentiated. The default value is 3 for the integral of cubic B-splines.


If TRUE, an intercept is included in the basis; Default is FALSE.


Boundary points at which to anchor the B-spline basis to be differentiated. By default, they are the range of the non-NA data. If both knots and Boundary.knots are supplied, the basis parameters do not depend on x.


Optional arguments for future usage.


A matrix of dimension length(x) by df = degree + length(knots) (plus on if intercept is included). Attributes that correspond to the arguments specified are returned for usage of other functions in this package.


The function is similar with splineDesign. However, it provides a more user-friendly interface, a more considerate NA's handling. Internally, it calls bSpline and generates a basis matrix for representing the family of piecewise polynomials and their corresponding derivative with the specified interior knots and degree, evaluated at the values of x. The function splineDesign in splines package can also be used to calculate derivative of B-splines.


De Boor, Carl. (1978). A practical guide to splines. Vol. 27. New York: Springer-Verlag.

See also

predict.dbs for evaluation at given (new) values; deriv.dbs for derivative method; bSpline for B-splines; ibs for integral of B-splines.


library(splines2) x <-, 1, 0.01) knots <- c(0.2, 0.4, 0.7) ## the second derivative of cubic B-splines with three internal knots dMat <- dbs(x, derivs = 2L, knots = knots, intercept = TRUE) ## compare with the results from splineDesign ord <- attr(dMat, "degree") + 1L bKnots <- attr(dMat, "Boundary.knots") aKnots <- c(rep(bKnots[1L], ord), knots, rep(bKnots[2L], ord)) res <- splines::splineDesign(aKnots, x = x, derivs = 2L) stopifnot(all.equal(res, dMat, check.attributes = FALSE))