# find.c: Work Function for 'smoothSurvReg' In smoothSurv: Survival Regression with Smoothed Error Distribution

 find.c 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 mu. `sdspline` Standard deviation sigma0 of the basis G-spline. `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")
```

smoothSurv documentation built on April 18, 2022, 5:06 p.m.