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

### Description

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

### Usage

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

### Arguments

`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.

### Details

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.

### Value

`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).

### Note

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

### See Also

Fitting function `sscden` and `dsscden`.

[Package gss version 2.1-7 Index]