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coef
to the plot()
method for splines2
objects, allowing visualization of the fitted spline function with a given coefficient vector.@docType package
documentation.nsk()
for natural cubic spline basis functions following the function survival::nsk()
(introduced in survival package version 3.2-8).plot()
methods to quickly visualize the spline basis functions.$
method to extract an attribute of the returned splines2
object.periodic
to bSpline()
for periodic B-splines and a new class named PeriodicBSpline
to the Rcpp interface: issue 19.coef
to the predict()
methods to compute the responding spline function and made it possible to obtain the derivatives or update spline basis functions by passing ...
to the update()
methods.trim
to naturalSpline()
to set the default boundary knots after trimming a fraction of observations.warn.outside
and a package option named splines2.warn.outside
to specify if a warning should be thrown out for B-splines, etc. when any x
is placed outside the boundary.bsp()
= bSpline()
msp()
= mSpline()
isp()
= iSpline()
csp()
= cSpline()
nsp()
= naturalSpline()
bpoly()
= bernsteinPoly()
H
to the attribution of objects for natural cubic splines so that users may transform cubic B-splines (from other software/packages) to the natural cubic splines (returned by naturalSpline()
/nsp()
or nsk()
). df
to be equidistant if the internal knots resulting from quantiles are problematic. A warning will be thrown out in that case.PeriodicMSpline
so that a simple knot sequence can be specified through set_knot_sequence
: issue 18.update()
methods to produce new spline basis functions based on the given object with specified updates in terms of degree
and knots
, etc.splines2
to the output matrices to simplify some common S3 methods.x
(by replacing the naive binary search implementation with std::upper_bound
and std::distance
).makepredictcall()
methods for all available spline basis functions to help model.frame.default()
create the right matrices when predicting from models with terms such as bSpline()
, etc. Thanks Zheyuan Li for suggesting this feature.derivs
and integal
to bSpline()
for consistency with mSpline()
and bernsteinPoly()
, etc.predict()
method for cSpline
objects when scale = FALSE
.BernsteinPoly
and PeriodicMSpline
objects to the C++ interface.knots()
methods to extract internal knots and boundary knots from a given splines2 object.length(knots) >= degree
to length(knots) >= degree - 1
.naturalSpline()
providing implementation of nonnegative natural cubic splines.periodic
to function mSpline()
for periodic M-splines.integral
to function mSpline()
for integrals of M-splines or periodic M-splines.deriv()
, predict()
, and print()
method for naturalSpline
class object.deriv()
method for mSpline
class object for periodic M-splines.bernsteinPoly()
providing implementation of generalized Bernstein polynomials.intercept
in function iSpline()
and cSpline()
to TRUE
for a complete set of spline basis functions in shape-restricted regression.iSpline()
and cSpline()
.bSpline()
.deriv.mSpline()
method for third derivatives of scaled C-splines.df
for piecewise constant basis functions when knots = NULL
.deriv.cSpline()
method for derivatives of order greater than two when scale = TRUE
.dbs()
generating derivative of given order of B-splines. It is a similar function with splines::splineDesign()
. However, it provides a more user-friendly interface and more consistent handling on NA
’s.deriv()
methods for derivatives of given order of any existing splines2 object that can be generated currently.derivs
to function mSpline()
and iSpline()
for derivatives.bSpline()
generating B-spline basis allowing zero degree or piecewise constant basis based on function bs()
in the splines package.bSpline()
to allow M-splines of degree zero.cSpline()
constructing convex spline (C-spline) basis.predict()
methods for bSpline2
object and cSpline
object generated by bSpline()
and cSpline()
, respectively.print()
methods for all splines2 objects developed so far.iSpline()
to construct I-spline basis directly from B-spline basis instead of M-spline basis.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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