Description Usage Arguments Value Note Author(s) References See Also Examples

Predicted values from a local polynomials of degree less than 2.

Missing values are not allowed.

1 2 |

`x` |
A numeric vector of explanatory variable of length |

`y` |
A numeric vector of variable to be explained of length |

`criterion` |
Character string. If the bandwidth
( |

`bandwidth` |
The kernel bandwidth smoothing parameter (a numeric vector of either length 1). |

`kernel` |
Character string which allows to choose between gaussian kernel
( |

`control.par` |
A named list that control optional parameters. The
two components are |

`cv.options` |
A named list which controls the way to do cross
validation with component |

Returns an object of class `npregress`

which is a list including:

`bandwidth` |
The kernel bandwidth smoothing parameter. |

`residuals` |
Vector of residuals. |

`fitted` |
Vector of fitted values. |

`df` |
The effective degree of freedom of the smoother. |

`call` |
A list containing four components: |

`criteria` |
either a named list containing the bandwidth search
grid and all the criteria ( |

See `locpoly`

for fast binned implementation
over an equally-spaced grid of local polynomial. See `ibr`

for univariate and **multivariate** smoothing.

Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.

Wand, M. P. and Jones, M. C. (1995). *Kernel Smoothing*. Chapman and Hall, London.

`predict.npregress`

,
`summary.npregress`

,
`locpoly`

, `ibr`

1 2 3 4 5 6 7 8 9 10 11 12 |

```
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-20. For overview type 'help("mgcv-package")'.
Residuals:
Min 1Q Median 3Q Max
-0.32219 -0.09171 0.01530 0.09731 0.27988
Residual standard error: 0.1453 on 80.4 degrees of freedom
user
"No Informative Criterion"
Kernel: gaussian (with 19.6 df)
Bandwidth: 0.02 chosen by user
```

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