dsscden: Evaluating PDF, CDF, and Quantiles of Smoothing Spline...

In gss: General Smoothing Splines

Evaluating PDF, CDF, and Quantiles of Smoothing Spline Conditional Density Estimates

Description

Evaluate pdf, cdf, and quantiles for smoothing spline conditional density estimates.

Usage

dsscden(object, y, x)
psscden(object, q, x)
qsscden(object, p, x)
d.sscden(object, x, y)
d.sscden1(object, x, y, scale=TRUE)

Arguments

object	Object of class "sscden" or "sscden1".
x	Data frame of x values on which conditional density f(y|x) is to be evaluated.
y	Data frame or vector of points on which conditional density f(y|x) is to be evaluated.
q	Vector of points on which cdf is to be evaluated.
p	Vector of probabilities for which quantiles are to be calculated.
scale	Flag indicating whether to use approximate scaling without quadrature.

Details

The arguments x and y are of the same form as the argument newdata in predict.lm, but y in dsscden can take a vector for 1-D responses.

psscden and qsscden naturally only work for 1-D responses.

Value

A matrix or vector of pdf, cdf, or quantiles of f(y|x), with each column corresponding to a distinct x value.

See Also

Fitting function sscden and cdsscden.

gss documentation built on Oct. 12, 2024, 1:08 a.m.