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

Simulate a two-regime TAR model.

1 2 |

`object` |
a TAR model fitted by the tar function; if it is supplied, the model parameters and initial values are extracted from it |

`ntransient` |
the burn-in size |

`n` |
sample size of the simulated series |

`Phi1` |
the coefficient vector of the lower-regime model |

`Phi2` |
the coefficient vector of the upper-regime model |

`thd` |
threshold |

`d` |
delay |

`p` |
maximum autoregressive order |

`sigma1` |
noise std. dev. in the lower regime |

`sigma2` |
noise std. dev. in the upper regime |

`xstart` |
initial values for the simulation |

`e` |
standardized noise series of size equal to length(xstart)+ntransient+n; if missing, it will be generated as some normally distributed errors |

The two-regime Threshold Autoregressive (TAR) model is given by the following formula:

*
Y_t = φ_{1,0}+φ_{1,1} Y_{t-1} +…+ φ_{1,p} Y_{t-p_1} +σ_1 e_t,
\mbox{ if } Y_{t-d}≤ r *

* Y_t = φ_{2,0}+φ_{2,1} Y_{t-1} +…+φ_{2,p_2} Y_{t-p}+σ_2 e_t,
\mbox{ if } Y_{t-d} > r.*

where r is the threshold and d the delay.

A list containing the following components:

`y` |
simulated TAR series |

`e` |
the standardized errors |

...

Kung-Sik Chan

Tong, H. (1990) "Non-linear Time Series, a Dynamical System Approach," Clarendon Press Oxford "Time Series Analysis, with Applications in R" by J.D. Cryer and K.S. Chan

1 2 3 4 5 |

TSA documentation built on July 2, 2018, 1:04 a.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.