get_error {ushr}

Evaluate error metric between data and model prediction

Description

For a given parameter set, this function computes the predicted viral load curve and evaluates the error metric between the prediction and observed data (to be passed to optim).

Usage

get_error(params, param_names, free_param_index, data, model_list,
  inv_param_transform_fn)

Arguments

params

named vector of the parameters from which the model prediction should be generated.

param_names

names of parameter vector.

free_param_index

logical TRUE/FALSE vector indicating whether the parameters A, delta, B, gamma are to be recovered. This should be c(TRUE, TRUE, TRUE, TRUE) for the biphasic model and c(FALSE, FALSE, TRUE, TRUE) for the single phase model.

data

dataframe with columns for the subject's viral load measurements ('vl'), and timing of sampling ('time')

model_list

character indicating which model is begin fit. Can be either 'four' for the biphasic model, or 'two' for the single phase model.

inv_param_transform_fn

list of transformation functions to be used when back-transforming the transformed parameters. Should be the inverse of the forward transformation functions. Defaults to exponential.