predict_ode.survFit: Predict method for 'survFit' objects

In morse: Modelling Reproduction and Survival Data in Ecotoxicology

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 class 'survFit'
predict_ode(
  object,
  data_predict = NULL,
  spaghetti = FALSE,
  mcmc_size = 1000,
  hb_value = TRUE,
  interpolate_length = 100,
  interpolate_method = "linear",
  hb_valueFORCED = NA,
  ...
)

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

Value

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

Examples

# (1) Load the survival data
data("propiconazole_pulse_exposure")

# (2) Create an object of class "survData"
dataset <- survData(propiconazole_pulse_exposure)


# (3) Run the survFit function
out <- survFit(dataset , model_type = "SD")

# (4) Create a new data table for prediction
data_4prediction <- data.frame(time = 1:10,
                               conc = c(0,5,30,30,0,0,5,30,15,0),
                               replicate= rep("predict", 10))

# (5) Predict on a new data set
predict_out <- predict_ode(object = out, data_predict = data_4prediction,
                           mcmc_size = 1000, spaghetti = TRUE)

morse documentation built on Oct. 29, 2022, 1:14 a.m.