Description Usage Arguments Value See Also Examples

View source: R/Simulation_Based_Calibration.R

Draw a dataset and MCMC samples.

1. draw a model parameter from prior distribution,

2. draw a dataset from the model with the parameter drawn in step 1,

3. draw a collection of posterior samples for the dataset drawn in step 2.

1 2 3 4 5 6 7 8 9 10 11 12 13 |

`sd` |
Standard Deviation of priors |

`C` |
No. of Confidence levels |

`seed.for.drawing.a.prior.sample` |
seed |

`fun` |
An one dimensional real valued function defined on the parameter space. This is used in the definition of the rank statistics. Generally speaking, the element of the parameter space is a vector, so the function should be defined on vectors. In my model parameter is mean, standard deviation, C thresholds of the latent Gaussian, so this function should be defined on the C+2 dimensional Euclidean space. |

`NI` |
No. of images |

`NL` |
No. of Lesions |

`initial.seed.for.drawing.a.data` |
seed |

`ModifiedPoisson` |
Logical, that is If .
per lesionSimilarly, If .
per imageFor more details, see the author's paper in which I explained If
where On the other hand, if
where The model is fitted so that
the estimated FROC curve can be ragraded
as the expected pairs of FPF per image and TPF per lesion ( or as the expected pairs of FPF per image and TPF per lesion ( If On the other hand, if So,data of FPF and TPF are changed thus, a fitted model is also changed whether Revised 2019 Dec 8 Revised 2019 Nov 25 Revised 2019 August 28 |

`PreciseLogLikelihood` |
Logical, that is |

`ite` |
A variable to be passed to the function |

`DrawCurve` |
Logical: |

Draw.a.prior.sample The Return value of `Draw_a_prior_sample`

A dataList and an object of the stanfit S4 class with respect to the dataList

hits_false_alarms_creator_from_thresholds

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ```
## Not run:
# Draw a curve for various seeds and various number of confidence levels.
# Changing the seed, we can draw a parameter from priors and using this sample,
# we can draw the datasets from our model whose parameters are
# the priors samples.
# 1. draw a model parameter from prior distribution,
# 2. draw a dataset from the model with the parameter drawn in step 1,
# 3. draw a collection of posterior samples for the dataset drawn in step 2.
Draw_a_simulated_data_set_and_Draw_posterior_samples(
seed.for.drawing.a.prior.sample = 1234,
C=8)
Draw_a_simulated_data_set_and_Draw_posterior_samples(
seed.for.drawing.a.prior.sample = 12345,
C=7)
Draw_a_simulated_data_set_and_Draw_posterior_samples(
seed.for.drawing.a.prior.sample = 123456,
C=6)
Draw_a_simulated_data_set_and_Draw_posterior_samples(
seed.for.drawing.a.prior.sample = 1234567,
C=5)
## End(Not run)# dottest
``` |

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