R: Spline Smoothed Distribution

ssd {fBasics} | R Documentation

## Spline Smoothed Distribution

### Description

Density, distribution function, quantile function and random generation from smoothing spline estimates.

### Usage

    dssd(x, param, log = FALSE)
    pssd(q, param)
    qssd(p, param)
    rssd(n, param)

### Arguments

`param` | an object as returned by the function `ssdFit`..
`log` | a logical flag by default `FALSE`. Should labels and a main title drawn to the plot?
`n` | number of observations.
`p` | a numeric vector of probabilities.
`x, q` | a numeric vector of quantiles.

### Value

All values for the `*ssd` functions are numeric vectors: `d*` returns the density, `p*` returns the distribution function, `q*` returns the quantile function, and `r*` generates random deviates.

All values have attributes named `"param"` listing the values of the distributional parameters.

### 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]