# predict.fahrmeier_94

##### Predict function for the result of `ddhazard`

Predict function for the result of `ddhazard`

##### Usage

`"predict"(object, new_data, type = c("response", "term"), tstart = "start", tstop = "stop", use_parallel = F, sds = F, max_threads = getOption("ddhazard_max_threads"), ...)`

##### Arguments

- object
- Result of a
`ddhazard`

call - new_data
- New data to base predictions on
- type
- Either
`"response"`

for predicted probability of death or`"term"`

for predicted terms in the linear predictor - tstart
- Name of the start time column in
`new_data`

. It must corresponds to tstart used in the`Surv(tstart, tstop, event)`

in the`formula`

passed to`ddhazard`

- tstop
- same as
`tstart`

for the stop argument - use_parallel
`TRUE`

if computation for`type = "response"`

should be computed in parallel with the`parallel`

package- sds
`TRUE`

if point wise standard deviation should be computed. Convenient if you use functions like`ns`

and you only want one term per term in the right hand site of the`formula`

used in`ddhazard`

- max_threads
- Maximum number of threads to use. -1 if it should be determined by a call to
`detectCores`

- ...
- Not used

##### Term

The result of `type = "term"`

is a list with the following elements

`terms` ` ` |

Is a 3D array. The first dimension is the number of bins, the second dimension is rows in `new_data` and the last dimension is the state space terms |

`sds` ` ` |

Similar to `terms` for the point wise confidence intervals using the smoothed co-variance matrices |

##### Response

The result of `type = "response"`

is a list with the elements below. The function check if there are columns in `new_data`

which's names match `tstart`

and `tstop`

. If not, then each row in new data will get a predicted probability of dying in every bin.

`fits` ` ` |

Fitted probability of dying |

`istart` ` ` |

Vector with the index of the first bin the elements in `fits` is in |

*Documentation reproduced from package dynamichazard, version 0.1.0, License: GPL-2*

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