get_error_triphasic

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

params

param_names

logical TRUE/FALSE vector indicating whether the parameters A, delta, A_b, delta_b, B, gamma are to be recovered. This should be c(TRUE, TRUE, TRUE, TRUE, TRUE, TRUE) for the triphasic model.

free_param_index

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

data

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.

inv_param_transform_fn

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).

Analyzes longitudinal data of HIV decline in patients on antiretroviral therapy using the canonical biphasic exponential decay model (pioneered, for example, by work in Perelson et al. (1997) <doi:10.1038/387188a0>; and Wu and Ding (1999) <doi:10.1111/j.0006-341X.1999.00410.x>). Model fitting and parameter estimation are performed, with additional options to calculate the time to viral suppression. Plotting and summary tools are also provided for fast assessment of model results.

get_error_triphasic: Evaluate error metric between data and model prediction

Description

Usage

Arguments