Description Usage Arguments Value References Examples

This is a wrapper function calling C++ code that executes a pivotal analysis to deliver double sided confidence bounds at the B-value quantiles for the model distribution. The bounds are presented as log values for X axis plotting suitable for transformation to a specific linear fit to data of the same size. The pivotal points are expected to be the basis for a curve generation upon ultimate display.

1 |

`x` |
The quantity of complete failures for evaluation, or an event vector |

`CI` |
The double sided confidence interval of interest. |

`S` |
The number of random samples to be drawn for Monte Carlo simulation. S must be a multiple of 10, not less than 1,000. The default of 10^4 is adequate for most instances. S is implemented as an unsigned int in C++ code. The maximum limit is 4x10^9 if system memory permits. |

`Bval` |
A vector of B-values at which to determine the confidence bounds. |

`Eta` |
The Eta parameter to be used in random sampling. Default = 1.0 |

`Beta` |
The Beta parameter to be used in random sampling. Default = 1.0 |

`model` |
A character string representing the model of interest. The default value of "w2" for 2-parameter Weibull is the only model currently valid. |

`seed` |
an integer used to set the RNG seed. Default = 1234 |

`ProgRpt` |
A boolean value to control the generation of percent completion feedback in the R terminal. |

Returns a dataframe holding the Lower bound, the Median, and the Upper bound according to the sequence of B-values provided.

Dr. Robert B. Abernethy, (2008) "The New Weibull Handbook, Fifth Edition"

1 | ```
bounds<-CBpiv(10,0.9)
``` |

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