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