eval.Gspline: Evaluate a G-spline in a grid of values

In smoothSurv: Survival Regression with Smoothed Error Distribution

Evaluate a G-spline in a grid of values

Description

This function computes values of

f(x) = sum[j=1][g] c[j]*phi(x; mu[j],sigma[j]^2)

in a grid of x values.

In above expression, phi(x; mu[j],sigma[j]^2) denotes a density of N(mu[j], sigma[j]^2).

Usage

  eval.Gspline(Gspline, grid)

Arguments

Gspline	A data frame with at least three columns named “Knot”, “SD basis” and “c coef.” which determine mu[1], ..., mu[g], sigma[1], ..., sigma[g] and c[1], ..., c[g]. Data.frame with such properties can be found e.g. as spline component of the resulting object returned by functions smoothSurvReg and minPenalty.
grid	A numeric vector giving the grid of x values at which the G-spline is to be evaluated.

Value

A data.frame with columns named “x” (grid) and “y” (G-spline values).

Author(s)

Arnošt Komárek [e-mail]

Examples

  spline <- minPenalty(knots=seq(-4.2, 4.2, by=0.3), sdspline=0.2, difforder=3)$spline
  values <- eval.Gspline(spline, seq(-4.5, 4.5, by=0.05))
  plot(values, type="l", bty="n", lwd=3)

smoothSurv documentation built on Oct. 11, 2022, 1:05 a.m.