Description Usage Arguments Details Value References See Also Examples

View source: R/622.Poster_Predictive_x.R

The Predicted probability - Bayesian approach

1 | ```
probPREx(x, n, xnew, m, a1, a2)
``` |

`x` |
- Number of successes |

`n` |
- Number of trials from data |

`xnew` |
- Required size of number of success |

`m` |
- Future :Number of trials |

`a1` |
- Beta Prior Parameters for Bayesian estimation |

`a2` |
- Beta Prior Parameters for Bayesian estimation |

Computes posterior predictive probability for the required size of number of
successes for `xnew`

of `m`

trials from the given number of successes `x`

of `n`

trials for the given parameters for Beta prior distribution

A dataframe with x,n,xnew,m,preprb

`x` |
Number of successes |

`n` |
Number of trials |

`xnew` |
Required size of number of success |

`m` |
Future - success, trails |

`preprb ` |
The predicted probability |

[1] 2002 Gelman A, Carlin JB, Stern HS and Dunson DB Bayesian Data Analysis, Chapman & Hall/CRC

Other Miscellaneous functions for Bayesian method: `empericalBAx`

,
`empericalBA`

, `probPOSx`

,
`probPOS`

, `probPRE`

1 2 | ```
x=0; n=1; xnew=10; m=10; a1=1; a2=1
probPREx(x,n,xnew,m,a1,a2)
``` |

proportion documentation built on May 19, 2017, 7:40 a.m.

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