# Additive nonlinear autoregressive model

### Description

Additive nonlinear autoregressive model.

### Usage

1 | ```
aar(x, m, d=1, steps=d, series)
``` |

### Arguments

`x` |
time series |

`m, d, steps` |
embedding dimension, time delay, forecasting steps |

`series` |
time series name (optional) |

### Details

Nonparametric additive autoregressive model of the form:

*
x[t+steps] = mu + sum_j s_j(x[t-(j-1)d])
*

where *s_j* are nonparametric univariate functions of lagged time
series values. They are represented by cubic regression splines.
*s_j* are estimated together with their level of
smoothing using routines in the mgcv package (see references).

### Value

An object of class `nlar`

, subclass `aar`

, i.e. a list
with mostly internal structures for the fitted `gam`

object.

### Author(s)

Antonio, Fabio Di Narzo

### References

Wood, mgcv:GAMs and Generalized Ridge Regression for R. R News 1(2):20-25 (2001)

Wood and Augustin, GAMs with integrated model selection using penalized regression splines and applications to environmental modelling. Ecological Modelling 157:157-177 (2002)

### Examples

1 2 3 4 5 6 |