Get expected variance/sd/ci of dependent variable based on PKPDsim model, parameters, and regimen

Usage

get_var_y(
  model = NULL,
  parameters = list(),
  regimen = list(),
  t_obs = c(1:48),
  obs_comp = NULL,
  obs_variable = NULL,
  omega = c(0.1, 0.05, 0.1),
  omega_full = NULL,
  n_ind = NULL,
  ruv = NULL,
  y = NULL,
  rel_delta = 1e-04,
  method = "delta",
  sequence = NULL,
  auc = FALSE,
  sd = TRUE,
  q = NULL,
  in_parallel = FALSE,
  n_cores = 3,
  return_all = FALSE,
  ...
)

Arguments

model: model, created using `PKPDsim::new_ode_model()`
parameters: parameters list
regimen: regimen, as created using `PKPDsim::new_regimen()`
t_obs: vector of observation times
obs_comp: observation compartment. If NULL will be "obs" (default)
obs_variable: observation variable. If NULL, will be ignored, otherwise will override `obs_comp`.
omega: triangle omega block
omega_full: full omega block
n_ind: number of individuals to simulate with sim method
ruv: residual variability, supplied as a named list, ex: `list(prop = 0, add = 0, exp = 0)`
y: vector of observations. If NULL, then a new simulation will be performed.
rel_delta: rel_delta
method: method, `delta` or `sim`
sequence: for simulations, if not NULL the pseudo-random sequence to use, e.g. "halton" or "sobol". See `mvrnorm2` for more details.
auc: is AUC?
sd: return as standard deviation (`TRUE`) or variance (`FALSE`)
q: return vector of quantiles instead of sd/var. Will return parametric quantiles when delta-method is used, non-parametric for simulation-based methods.
in_parallel: run simulations in parallel?
n_cores: if run in parallel, on how many cores?
return_all: return object with all relevant information?
...: passed on to `sim_ode()`

Value

Vector of standard deviations or variances (or quantiles thereof) for dependent value variable