Description Usage Arguments Details Value Author(s) Examples

Find mixture proportions that approximate given distribution by a G-spline mixture.

1 |

`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. |

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`

.

Either the vector of G-spline 'c' coefficients or `NULL`

if there are problems to find them.

Arnošt Komárek arnost.komarek[AT]mff.cuni.cz

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
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")
``` |

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