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

cdssden {gss} | R Documentation

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

### Description

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

### Usage

    cdssden(object, x, cond, int=NULL)
    cpssden(object, q, cond)
    cqssden(object, p, cond)

### Arguments

`object` | Object of class `"ssden"`.
`x` | Data frame or vector of points on which conditional density is to be evaluated.
`cond` | One row data frame of conditioning variables.
`int` | Normalizing constant.
`q` | Vector of points on which conditional cdf is to be evaluated.
`p` | Vector of probabilities for which conditional quantiles are to be calculated.

### Details

The argument `x` in `cdssden` is of the same form as the argument `newdata` in `predict.lm`, but can take a vector for 1-D conditional densities.

`cpssden` and `cqssden` naturally only work for 1-D conditional densities of a numerical variable.

### Value

`cdssden` returns a list object with the following elements.

`pdf` | Vector of conditional pdf.
`int` | Normalizing constant.

`cpssden` and `cqssden` return a vector of conditional cdf or quantiles.

### Note

If variables other than factors or numerical vectors are involved in `x`, the normalizing constant can not be computed.

### See Also

Fitting function `ssden` and `dssden`.

[Package gss version 2.2-2 Index]