https://github.com/cran/fBasics
Revision ac00e3733757e14face419a377dfa956aedf2abe authored by Tobias Setz on 17 June 2022, 09:50:58 UTC, committed by cran-robot on 17 June 2022, 09:50:58 UTC
1 parent 40815ac
Tip revision: ac00e3733757e14face419a377dfa956aedf2abe authored by Tobias Setz on 17 June 2022, 09:50:58 UTC
version 3042.89.2
version 3042.89.2
Tip revision: ac00e37
dist-ssdFit.Rd
\name{ssdFit}
\alias{ssdFit}
\title{Fit Density Using Smoothing Splines }
\description{
Estimates the parameters of a density function
using smoothing splines.
}
\usage{
ssdFit(x)
}
\arguments{
\item{x}{
a numeric vector.
}
}
\value{
The function \code{ssdFit}, \code{hypFit} returns an object of class
\code{ssden}.
The returned object can be used to evaluate density, probabilities
and quantiles.
}
\author{
Diethelm Wuertz, Chong Gu for the underlying \code{gss} package.
}
\references{
Gu, C. (2002),
\emph{Smoothing Spline ANOVA Models},
New York Springer--Verlag.
Gu, C. and Wang, J. (2003),
\emph{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)
}
\keyword{distribution}
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