Helper function used to fit a QRNN model via the nlm() function and a variant of the finite smoothing algorithm.

1 2 3 |

`x` |
covariate matrix with number of rows equal to the number of samples and number of columns equal to the number of variables. |

`y` |
predictand column matrix with number of rows equal to the number of samples. |

`n.hidden` |
number of hidden nodes in the QRNN model. |

`tau` |
desired tau-quantile. |

`iter.max` |
maximum number of iterations of the optimization algorithm. |

`n.trials` |
number of repeated trials used to avoid local minima. |

`bag` |
logical variable indicating whether or not bootstrap aggregation (bagging) should be used. |

`lower` |
left censoring point. |

`eps.seq` |
sequence of |

`Th` |
hidden layer transfer function; use |

`Th.prime` |
derivative of the hidden layer transfer function |

`penalty` |
weight penalty for weight decay regularization. |

`trace` |
logical variable indicating whether or not diagnostic messages are printed during optimization. |

`...` |
additional parameters passed to the |

a list containing elements

`W1` |
matrix of optimized input-hidden layer weights. |

`W2` |
matrix of optimized hidden-output layer weights. |

`qrnn.cost`

, `qrnn.fit`

, `qrnn.eval`

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