predict.qss {quantreg} | R Documentation |

## Predict based on nonparametric quantile regression smoothing
spline component

### Description

Additive models for nonparametric quantile regression using total
variation penalty methods can be fit with the `rqss`

function. Univarariate and bivariate components can be predicted
using these functions.

### Usage

predict.qss1(object, newdata, ...)
predict.qss2(object, newdata, ...)

### Arguments

`object` |
is a fitted object produced by `rqss` |

`newdata` |
a data frame describing the observations at which
prediction is to be made |

`...` |
optional arguments |

### Details

For both univariate and bivariate prediction linear interpolation is
done. In the bivariate case, this involves computing barycentric
coordinates of the new points relative to their enclosing triangles.

### Value

A list consisting of x and y components in the case of qss1,
and a list consisting of x, y, and z components in the case of qss2.
In the former case the y component constitutes the predictions at x,
and in the latter, z is the vector of the predictions at the points
(x,y).

### Author(s)

R. Koenker

### See Also

`rqss`

### Examples

[Package

*quantreg* version 3.82

Index]