Description Usage Arguments Value Examples

View source: R/count_alarms_hetero_faster.R

Function that divides `load_training`

into quantiles using `bins`

as the number
of quantiles.
For each quantile the mean and standard deviation are calculated. A spline is fitted to the
means and two splines are fitted to three sigma above and below the means, respectively.
The function generates alarms when the test data fall outside the band of three sigma.
The function generates a plot by default, and can also show the summary of the quantiles if
`show_summary = TRUE`

.

1 2 3 | ```
count_alarms_hetero_faster(load_training, vib_training, knots, load_test,
vib_test, show_figure = TRUE, show_summary = FALSE, bins = 160,
load_min = 0)
``` |

`load_training` |
A vector containing the training data of the load variables such as power or generator speed. |

`vib_training` |
A vector containing the training data of the vibration signal. |

`knots` |
A vector containing the locations of the knots. |

`load_test` |
A vector with the test data of the load variable. |

`vib_test` |
A vector with the test data of the vibration signal. |

`show_figure` |
A logical vector indicating if a plot should be made. |

`show_summary` |
A logical vector stating whether the quantile summaries should be shown or not. |

`bins` |
The number of bins used. |

`load_min` |
The minimum load to be used. |

A list of the count of the number of alarms, alarm rate, and residuals. Furthermore a plot is
generated by default, set by `show_figure`

.

`count` |
A count of the number of alarms in the test set. |

`alarm_rate` |
The alarm rate in the test set. |

`residuals` |
The residuals in the test set. |

1 2 |

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