lp {locfit} | R Documentation |

## Local Polynomial Model Term

### Description

`lp`

is a local polynomial model term for Locfit models.
Usually, it will be the only term on the RHS of the model formula.

Smoothing parameters should be provided as arguments to `lp()`

,
rather than to `locfit()`

.

### Usage

```
lp(..., nn, h, adpen, deg, acri, scale, style)
```

### Arguments

`...` |
Predictor variables for the local regression model. |

`nn` |
Nearest neighbor component of the smoothing parameter.
Default value is 0.7, unless either |

`h` |
The constant component of the smoothing parameter. Default: 0. |

`adpen` |
Penalty parameter for adaptive fitting. |

`deg` |
Degree of polynomial to use. |

`acri` |
Criterion for adaptive bandwidth selection. |

`style` |
Style for special terms ( |

`scale` |
A scale to apply to each variable. This is especially important for
multivariate fitting, where variables may be measured in
non-comparable units. It is also used to specify the frequency
for |

### See Also

### Examples

```
data(ethanol, package="locfit")
# fit with 50% nearest neighbor bandwidth.
fit <- locfit(NOx~lp(E,nn=0.5),data=ethanol)
# bivariate fit.
fit <- locfit(NOx~lp(E,C,scale=TRUE),data=ethanol)
# density estimation
data(geyser, package="locfit")
fit <- locfit.raw(lp(geyser,nn=0.1,h=0.8))
```

*locfit*version 1.5-9.10 Index]