bpp-package |
Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance |

basicPlot |
Basic plot functions to illustrate prior and posterior densities when considering a time-to-event endpoint |

bpp |
Bayesian Predictive Power (BPP) for Normally Distributed Endpoint |

bpp_1interim |
Bayesian Predictive Power (BPP) for Normally Distributed Endpoint |

bpp_2interim |
Bayesian Predictive Power (BPP) for Normally Distributed Endpoint |

ddcp |
Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance |

dUniformNormalTails |
Density and CDF for Uniform Distribution with Normal tails |

estimate_posterior |
Posterior density conditional on known interim result |

estimate_posterior_nominator |
Posterior density conditional on interim result is proportional to the value of this function |

estimate_toIntegrate |
Product of posterior density and conditional power for known interim result |

FlatNormalPosterior |
Integrand to compute Bayesian Predictive Power when flat prior has been updated with likelihood |

interval_posterior_nominator |
Posterior density conditional on interim result, only known as interval, is proportional to the value of this function |

interval_posterior_nominator2 |
Posterior density conditional on two interim results, both only known as intervals, is proportional to the value of this function |

interval_toIntegrate |
Product of posterior density and conditional power for blinded interim result |

interval_toIntegrate2 |
Product of posterior density and conditional power for blinded interim result |

NormalNormalPosterior |
Normal-Normal Posterior in conjugate normal model, for known sigma |

post_power |
Conditional power conditioning on a blinded interim |

pts |
Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance |

pUniformNormalTails |
Density and CDF for Uniform Distribution with Normal tails |