predict_ode.survFit: Predict method for `survFit` objects

Description

This is the generic predict S3 method for the survFit class. It provides predicted survival rate for "SD" or "IT" models under constant or time-variable exposure.

Usage

# S3 method for survFit
predict_ode(
  object,
  data_predict = NULL,
  spaghetti = FALSE,
  mcmc_size = 1000,
  hb_value = TRUE,
  interpolate_length = 100,
  interpolate_method = "linear",
  hb_valueFORCED = NA,
  ...
)

Value

a list of data.frame with the quantiles of outputs in df_quantiles or all the MCMC chaines df_spaghetti

Arguments

object: An object of class survFit.
data_predict: A dataframe with three columns time, conc and replicate used for prediction. If NULL, prediction is based on x object of class survFit used for fitting.
spaghetti: If TRUE, return a set of survival curves using parameters drawn from the posterior distribution.
mcmc_size: Can be used to reduce the number of mcmc samples in order to speed up the computation. mcmc_size is the number of selected iterations for one chain. Default is 1000. If all MCMC is wanted, set argument to NULL.
hb_value: If TRUE, the background mortality hb is taken into account from the posterior. If FALSE, parameter hb is set to a fixed value. The default is TRUE.
interpolate_length: Length of the time sequence for which output is wanted.
interpolate_method: The interpolation method for concentration. See package deSolve for details. Default is linear.
hb_valueFORCED: If hb_value is FALSE, it fix hb.
...: Further arguments to be passed to generic methods