confband | R Documentation |

Confidence bands for transformation, distribution, survivor or cumulative hazard functions

```
## S3 method for class 'cotram'
confband(object, newdata, level = 0.95,
type = c("trafo", "distribution", "survivor", "cumhazard"),
smooth = FALSE, q = NULL, K = 20, cheat = K, ...)
```

`object` |
an object of class |

`newdata` |
a data frame of observations. |

`level` |
the confidence level. |

`type` |
the function to compute the confidence band for. |

`smooth` |
logical; if |

`q` |
quantiles at which to evaluate the model. |

`K` |
number of grid points the function is evaluated at
(in the absence of |

`cheat` |
number of grid points the function is evaluated at when
using the quantile obtained for |

`...` |
additional arguments to |

The function is evaluated at the count response or at `K`

grid points
and simultaneous confidence intervals are then interpolated in order to
construct the band.

For each row in `newdata`

the function and corresponding confidence
band evaluated at the count response (or `K`

or `cheat`

grid points)
is returned.

```
op <- options(digits = 4)
data("birds", package = "TH.data")
### fit count transformation model with cloglog link
m_birds <- cotram(SG5 ~ AOT + AFS + GST + DBH + DWC + LOG, data = birds,
method = "cloglog")
### compute asymptotic confidence bands for the distribution function
### for the first oberservation
confband(m_birds, newdata = birds[1, ], type = "distribution")
options(op)
```

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