Description Usage Arguments Value

`calibva.sampler`

takes in estimation of the underlying
cause of death distribution from training data, as well as a transition
matrix based on calibration data. Along with the prior values,
it will return a list of posterior samples for parameters of interest

1 2 3 4 | ```
calibva.sampler(test.cod, calib.cod = NULL, calib.truth = NULL, causes,
epsilon, alpha, beta, tau.vec, delta, gamma.init, ndraws, nchains = 1,
init.seeds = NULL, max.gamma = 75, sample.gamma = TRUE,
gamma.final = NULL)
``` |

`test.cod` |
will be a vector of length N, with each entry as the estimated COD (as a character)for indiv. i |

`calib.cod` |
is in the same format as test.cod, except for the calibration set |

`calib.truth` |
is a character vector with the true COD for each subject in the calibration set |

`causes` |
is a character vector with the names of the causes you are interested in. The order of the output vector p will correspond to this vector |

`epsilon` |
A numeric value for the epsilon in the prior |

`alpha` |
A numeric value for the alpha in the prior |

`beta` |
A numeric value for the beta in the prior |

`tau.vec` |
A numeric vector for the logsd for the sampling distributions of the gammas |

`delta` |
A numeric value for the delta in the prior |

`gamma.init` |
A numeric value for the starting value of gammas |

`ndraws` |
The number of posterior samples to take within each chain |

`nchains` |
The number of chains |

`init.seeds` |
An optional numeric vector, of length nchains, with the initial seeds for each chain |

`max.gamma` |
The maximum value gamma is allowed to take in posterior samples. Default is 75. |

a mcmc.list of length `nchains`

, where each element is a
`mcmc.object`

containing the posterior draws for a given chain

jfiksel/CalibratedVA documentation built on July 22, 2019, 7:16 p.m.

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