cExpQQ | R Documentation |

Exponential QQ-plot adapted for right censored data.

```
cExpQQ(data, censored, plot = TRUE, main = "Exponential QQ-plot", ...)
```

`data` |
Vector of |

`censored` |
A logical vector of length |

`plot` |
Logical indicating if the quantiles should be plotted in an exponential QQ-plot, default is |

`main` |
Title for the plot, default is |

`...` |
Additional arguments for the |

The exponential QQ-plot adapted for right censoring is given by

`( -\log(1-F_{km}(Z_{j,n})), Z_{j,n} )`

for `j=1,\ldots,n-1,`

with `Z_{i,n}`

the `i`

-th order statistic of the data and `F_{km}`

the Kaplan-Meier estimator for the CDF.
Hence, it has the same empirical quantiles as an ordinary exponential QQ-plot but replaces the theoretical quantiles `-\log(1-j/(n+1))`

by `-\log(1-F_{km}(Z_{j,n}))`

.

This QQ-plot is only suitable for right censored data.

In Beirlant et al. (2007), only a Pareto QQ-plot adapted for right-censored data is proposed. This QQ-plot is constructed using the same ideas, but is not described in the paper.

A list with following components:

`eqq.the` |
Vector of the theoretical quantiles, see Details. |

`eqq.emp` |
Vector of the empirical quantiles from the data. |

Tom Reynkens

Beirlant, J., Guillou, A., Dierckx, G. and Fils-Villetard, A. (2007). "Estimation of the Extreme Value Index and Extreme Quantiles Under Random Censoring." *Extremes*, 10, 151–174.

`ExpQQ`

, `cLognormalQQ`

, `cParetoQQ`

, `cWeibullQQ`

, `KaplanMeier`

```
# Set seed
set.seed(29072016)
# Pareto random sample
X <- rpareto(500, shape=2)
# Censoring variable
Y <- rpareto(500, shape=1)
# Observed sample
Z <- pmin(X, Y)
# Censoring indicator
censored <- (X>Y)
# Exponential QQ-plot adapted for right censoring
cExpQQ(Z, censored=censored)
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.