R: Fit Density Using Smoothing Splines

ssdFit {fBasics} | R Documentation

## Fit Density Using Smoothing Splines

### Description

Estimates the parameters of a density function using smoothing splines.

### Usage

    ssdFit(x)

### Arguments

`x` | a numeric vector.

### Value

The function `ssdFit`, `hypFit` returns an object of class `ssden`. The returned object can be used to evaluate density, probabilities and quantiles.

### Author(s)

Diethelm Wuertz, Chong Gu for the underlying `gss` package.

### References

Gu, C. (2002), Smoothing Spline ANOVA Models, New York Springer–Verlag.

Gu, C. and Wang, J. (2003), Penalized likelihood density estimation: Direct cross-validation and scalable approximation, Statistica Sinica, 13, 811–826.

### Examples

    ## ssdFit -
       set.seed(1953)
       r = rnorm(500)
       hist(r, breaks = "FD", probability = TRUE,
         col = "steelblue", border = "white")

    ## ssdFit -
       param = ssdFit(r)

    ## dssd -
       u = seq(min(r), max(r), len = 301)
       v = dssd(u, param)
       lines(u, v, col = "orange", lwd = 2)

[Package fBasics version 3042.89 Index]