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 \varphi_{\mu_j, \sigma_j^2}(x)

in a grid of x values.

In above expression, \varphi_{\mu_j, \sigma_j^2}(x) 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, \dots,\mu_g, \sigma_1, \dots, \sigma_g and c_1,\dots, 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 June 22, 2024, 11:11 a.m.