Description Usage Arguments Value Note Author(s) References Examples

Wrapper function for optimizing any combination of a given `seasonal.factor`

vector in NNS.ARMA. Minimum sum of squared errors (forecast-actual) is used to determine optimum across all NNS.ARMA methods.

1 2 | ```
NNS.ARMA.optim(variable, training.set, seasonal.factor, method = "seq",
negative.values = FALSE)
``` |

`variable` |
a numeric vector. |

`training.set` |
numeric; |

`seasonal.factor` |
integers; Multiple frequency integers considered for NNS.ARMA model, i.e. |

`method` |
options: ("comb", "seq"); |

`negative.values` |
logical; |

Returns a list containing a vector of optimal seasonal periods `$period`

, the minimum SSE value `$SSE`

, and the `$method`

identifying which NNS.ARMA method was used.

The number of combinations will grow prohibitively large, they should be kept to a minimum when `(method = "comb")`

.

`seasonal.factor`

containing an element too large will result in an error. Please reduce the maximum `seasonal.factor`

.

Fred Viole, OVVO Financial Systems

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" http://amzn.com/1490523995

1 2 3 4 5 6 7 8 9 10 11 12 | ```
## Nonlinear NNS.ARMA period optimization using 5 yearly lags on AirPassengers monthly data
## Not run:
nns.optims <- NNS.ARMA.optim(AirPassengers, training.set = 132, seasonal.factor = seq(12, 60, 12))
## End(Not run)
## Then use optimal parameters in NNS.ARMA
## Not run:
NNS.ARMA(AirPassengers, training.set=132, seasonal.factor = nns.optims$periods,
method = nns.optims$method)
## End(Not run)
``` |

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