mspline_plotdata: Data for plotting an M-spline function, showing how it is...

In survextrap: Bayesian Flexible Parametric Survival Modelling and Extrapolation

Data for plotting an M-spline function, showing how it is built up from its basis

Description

Data for plotting an M-spline function, showing how it is built up from its basis

Usage

mspline_plotdata(
  knots = NULL,
  bknot = 10,
  df = 10,
  degree = 3,
  bsmooth = TRUE,
  coefs = NULL,
  scale = 1,
  tmin = 0,
  tmax = 10
)

Arguments

knots	Vector of knot locations. If not supplied, df has to be specified. One of two rules is then used to choose the knot locations. If bknot is specified, a set of equally spaced knots between zero and bknot is used. Otherwise if obstimes is supplied, the knots are chosen as equally spaced quantiles of obstimes. The number of knots (excluding zero) is df - degree + 1 if bsmooth is TRUE, or df - degree - 1 otherwise.
bknot	Location of the final spline knot.
df	Desired number of basis terms, or "degrees of freedom" in the spline. If knots is not supplied, the number of knots is then chosen to satisfy this.
degree	Spline polynomial degree. Can only be changed from the default of 3 if bsmooth is FALSE.
bsmooth	If TRUE then the function is constrained to also have zero derivative and second derivative at the boundary.
coefs	Coefficients of the spline basis terms. These are normalised internally to sum to 1, if they do not already sum to 1.
scale	Scale parameter. After computing the standard M-spline function as a weighted sum of the basis terms, the function is multiplied by scale. The log of the scale is the parameter called alpha in the results of a survextrap model, the intercept of the linear model on the log hazard.
tmin	Minimum plotting time. Defaults to zero.
tmax	Maximum plotting time. Defaults to the highest knot.

Value

A data frame with values of the hazard at different times for different basis functions.

survextrap documentation built on June 10, 2025, 5:11 p.m.