Description Usage Arguments Value Examples

`update_prior`

uses the equation for the posterior:

*
φ(λ | R; N,P) = Pr(R|λ; N,P) φ(λ) /
\int Pr(R | λ'; N,P) φ(λ') d λ'
*

where *φ* is the prior and *Pr(R | λ; N, P)* is the
probability of R reports of heads given that people lie with probability
*λ*:

*
Pr(R | λ; N, P) = binom(N, (1-P) + λ P)
*

1 | ```
update_prior(heads, N, P, prior = stats::dunif, npoints = 1000)
``` |

`heads` |
Number of good outcomes reported |

`N` |
Total number in sample |

`P` |
Probability of |

`prior` |
Prior over lambda. A function which takes a vector of values between 0 and 1, and returns the probability density. The default is the uniform distribution. |

`npoints` |
How many points to integrate on? |

The probability density of the posterior distribution, as a one-argument function.

1 2 | ```
posterior <- update_prior(heads = 30, N = 50, P = 0.5, prior = stats::dunif)
plot(posterior)
``` |

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