`R/plot.R`

`plotRate.Rd`

Plot the baseline cumulative rate function for an `reReg`

object.

plotRate( x, newdata = NULL, frailty = NULL, showName = FALSE, type = c("unrestricted", "bounded", "scaled"), smooth = FALSE, control = list(), ... )

x | an object of class |
---|---|

newdata | an optional data frame contains variables to include in the calculation of the cumulative rate function. If omitted, the baseline rate function will be plotted. |

frailty | an optional vector to specify the shared frailty for |

showName | an optional logical value indicating whether to label the curves
when |

type | a character string specifying the type of rate function to be plotted.
Options are "unrestricted", "scaled", "bounded". See |

smooth | an optional logical value indicating whether to add a smooth curve
obtained from a monotone increasing P-splines implemented in package |

control | a list of control parameters. |

... | graphical parameters to be passed to methods.
These include |

A `ggplot`

object.

The `plotRate()`

plots the estimated baseline cumulative rate function
depending on the identifiability assumption.
When `type = "unrestricted"`

(default), the baseline cumulative rate function
is plotted under the assumption \(E(Z) = 1\).
When `type = "scaled"`

, the baseline cumulative rate function is plotted
under the assumption \(\Lambda(\min(Y^\ast, \tau)) = 1\).
When `type = "bounded"`

, the baseline cumulative rate function is plotted
under the assumption \(\Lambda(\tau) = 1\).
See `?reReg`

for the specification of the notations and underlying models.

The argument `control`

consists of options with argument defaults
to a list with the following values:

- xlab
customizable x-label, default value is "Time".

- ylab
customizable y-label, default value is empty.

- main
customizable title, default value is "Baseline cumulative rate function".

These arguments can also be specified outside of the `control`

list.

data(simDat) fm <- Recur(t.start %to% t.stop, id, event, status) ~ x1 + x2 fit <- reReg(fm, data = simDat, model = "cox|cox", B = 0) ## Plot both the baseline cumulative rate and hazard function plot(fit)## Plot baseline cumulative rate function plotRate(fit)plotRate(fit, smooth = TRUE)