Compare the empirical distribution of censored data `y`

to the
distributions of simulated/replicated data `yrep`

from the posterior
predictive distribution. See the **Plot Descriptions** section, below, for
details.

Although some of the other bayesplot plots can be used with censored
data, `ppc_km_overlay()`

is currently the only plotting function designed
*specifically* for censored data. We encourage you to suggest or contribute
additional plots at
github.com/stan-dev/bayesplot.

ppc_km_overlay(y, yrep, ..., status_y, size = 0.25, alpha = 0.7)

y | A vector of observations. See |
---|---|

yrep | An \(S\) by \(N\) matrix of draws from the posterior
predictive distribution, where \(S\) is the size of the posterior sample
(or subset of the posterior sample used to generate |

... | Currently unused. |

status_y | The status indicator for the observations from |

size, alpha | Passed to the appropriate geom to control the appearance of
the |

A ggplot object that can be further customized using the **ggplot2** package.

`ppc_km_overlay()`

Empirical CCDF estimates of each dataset (row) in

`yrep`

are overlaid, with the Kaplan-Meier estimate (Kaplan and Meier, 1958) for`y`

itself on top (and in a darker shade). This is a PPC suitable for right-censored`y`

. Note that the replicated data from`yrep`

is assumed to be uncensored.

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari,
A., and Rubin, D. B. (2013). *Bayesian Data Analysis.* Chapman & Hall/CRC
Press, London, third edition. (Ch. 6)

Kaplan, E. L. and Meier, P. (1958). Nonparametric estimation
from incomplete observations.
*Journal of the American Statistical Association*. 53(282), 457--481.
doi:10.1080/01621459.1958.10501452.

Other PPCs:
`PPC-discrete`

,
`PPC-distributions`

,
`PPC-errors`

,
`PPC-intervals`

,
`PPC-loo`

,
`PPC-overview`

,
`PPC-scatterplots`

,
`PPC-test-statistics`

color_scheme_set("brightblue") y <- example_y_data() # For illustrative purposes, (right-)censor values y > 110: status_y <- as.numeric(y <= 110) y <- pmin(y, 110) # In reality, the replicated data (yrep) would be obtained from a # model which takes the censoring of y properly into account. Here, # for illustrative purposes, we simply use example_yrep_draws(): yrep <- example_yrep_draws() dim(yrep)#> [1] 500 434# \donttest{ ppc_km_overlay(y, yrep[1:25, ], status_y = status_y)# }