R: Evaluating Conditional PDF, CDF, and Quantiles of Smoothing...

cdsscden {gss}

R Documentation

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

Evaluate conditional pdf, cdf, and quantiles of f(y1|x,y2) for smoothing spline conditional density estimates f(y|x).

cdsscden(object, y, x, cond, int=NULL)
cpsscden(object, q, x, cond)
cqsscden(object, p, x, cond)

`object`	Object of class `"sscden"` or `"sscden1"`.
`x`	Data frame of x values on which conditional density f(y1\|x,y2) is to be evaluated.
`y`	Data frame or vector of y1 points on which conditional density f(y1\|x,y2) is to be evaluated.
`cond`	One row data frame of conditioning variables y2.
`q`	Vector of points on which cdf is to be evaluated.
`p`	Vector of probabilities for which quantiles are to be calculated.
`int`	Vector of normalizing constants.

The arguments x and y are of the same form as the argument newdata in predict.lm, but y in cdsscden can take a vector for 1-D y1.

cpsscden and cqsscden naturally only work for 1-D y1.

cdsscden returns a list object with the following components.

`pdf`	Matrix or vector of conditional pdf f(y1\|x,y2), with each column corresponding to a distinct x value.
`int`	Vector of normalizing constants.

cpsscden and cqsscden return a matrix or vector of conditional cdf or quantiles of f(y1|x,y2).

If variables other than factors or numerical vectors are involved in y1, the normalizing constants can not be computed.