Description Usage Arguments Value

Generate a random time series (matrix). This is a utility typically used in a time series model simulate method and not called directly by the user.

1 2 3 |

`sampleT` |
an integer indicating the number of periods. |

`p` |
an integer indicating the number of series. |

`lags` |
an integer indicating the number of periods prior to the sample (initial data w0) for which random numbers should be generated. This is useful in ARMA models. |

`noise` |
Noise can be supplied. Otherwise it will be generated. If supplied it should be a list as described below under returned value. |

`Cov` |
The covariance of the noise process. If this is specified then sd
is ignored. A vector or scalar is treated as a diagonal matrix. For an object of class
TSestModel, if neither Cov nor sd are specified, then Cov is set to
the estimated covariance ( |

`sd` |
The standard deviation of the noise. This can be a vector. |

`noise.model` |
A TSmodel to be used for generating noise (not yet supported by SS methods). |

`noise.baseline` |
a constant or matrix to be added to noise. Alternately this can be a vector of length p, each value of which is treated as a constant to add to the coresponding noise series. |

`rng` |
The random number generator information needed to regenerate a simulation. |

`tf` |
a time frame to use for the generated matrix. (alternately use start and frequency) |

`start` |
a time start date to use for the generated matrix. |

`frequency` |
a time frequency to use for the generated matrix. |

A time series matrix.

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