ssd {fBasics}

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

x, q

a numeric vector of quantiles.

p

a numeric vector of probabilities.

n

number of observations.

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?

Details

dssd gives the density, pssd gives the distribution function, qssd gives the quantile function, and rssd generates random deviates.

Value

numeric vector

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)