Description Usage Arguments Value Examples

Compute and plot coverage of CI for different confidence level. Useful for fake data check.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
compute_coverage(
post_samples,
truth,
CI = seq(0, 1, 0.05),
type = c("eti", "hdi")
)
plot_coverage(
post_samples,
truth,
CI = seq(0, 1, 0.05),
type = c("eti", "hdi")
)
``` |

`post_samples` |
Matrix of posterior samples. Rows represent a sample and columns represent variables. |

`truth` |
Vector of true parameter values (should be the same length as the number of columns in |

`CI` |
Vector of confidence levels. |

`type` |
Type of confidence intervals: either "eti" (equal-tailed intervals) or "hdi" (highest density intervals). |

`compute_coverage`

returns a Dataframe containing coverage (and 95% uncertainty interval for the coverage) for different confidence level (nominal coverage).
`plot_coverage`

returns a ggplot of the coverage as the function of the nominal coverage with 95% uncertainty interval.

1 2 3 4 5 6 7 | ```
N <- 100
N_post <- 1e3
truth <- rep(0, N)
post_samples <- sapply(rnorm(N, 0, 1), function(x) {rnorm(N_post, x, 1)})
compute_coverage(post_samples, truth)
plot_coverage(post_samples, truth)
``` |

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