find.c {smoothSurv} | R Documentation |
Work Function for 'smoothSurvReg'
Description
Find mixture proportions that approximate given distribution by a G-spline mixture.
Usage
find.c(knots, sdspline, dist = "dnorm")
Arguments
knots |
A vector of G-spline knots |
sdspline |
Standard deviation |
dist |
A character string specifying the function used to compute a density of the distribution you want to approximate. |
Details
The function finds the G-spline coefficients that approximates
a density given by dist
in such sense that the value
of the G-spline is exactly equal to the value of that density
in knots
.
Value
Either the vector of G-spline 'c' coefficients or NULL
if there are problems to find them.
Author(s)
Arnošt Komárek arnost.komarek@mff.cuni.cz
Examples
knots <- seq(-4, 4, 0.5)
sd0 <- 0.3
ccoef <- find.c(knots, sd0, dist = "dstlogis")
### We plot the approximation together with the truth
###
grid <- seq(-4, 4, 0.05)
truth <- dstlogis(grid)
### Following lines compute the values of the approximation
grid.big <- matrix(grid, nrow = length(grid), ncol = length(knots))
knots.big <- matrix(knots, nrow = length(grid), ncol = length(knots), byrow = TRUE)
normals <- dnorm(grid.big, mean = knots.big, sd = sd0)
approx <- normals %*% ccoef
### Plot it
plot(grid, approx, type = "l", xlab = "y", ylab = "f(y)", bty = "n")
lines(grid, truth, lty = 2)
legend(-4, 0.35, c("approx", "truth"), lty = 1:2, bty = "n")
[Package smoothSurv version 2.6 Index]