Construct Emax prediction function from model object
Value
A function f with arguments data and params. The data
argument defaults to the data used to estimate the model, and the
params arugment defaults to the estimated parameter values. Both
can be customized, as long as data contains columns corresponding
to each of the variables used by the model, and params is a named
numeric vector of the appropriate length. The names for params
must exactly match the names of the vector returned by coef(mod).
The return value for f is a numeric vector of model predictions for
each row in data, evaluated at parameters params.
Examples
mod <- emax_nls(
structural_model = rsp_1 ~ exp_1,
covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1),
data = emax_df
)
par <- coef(mod)
# customizable emax function with the same structural
# model and same covariate model, defaulting to the
# same data and parameters as the original model, but
# allowing user to pass their own data and parameters
mod_fn <- emax_fun(mod)
# apply the function to a few rows of the original data
mod_fn(
data = emax_df[120:125, ],
param = par
)
#> [1] 14.650737 8.467557 13.263190 15.728956 6.255590 13.622004
# adjust the parameters
new_par <- par
new_par["E0_Intercept"] <- 0
# simulate the model with the adjusted parameters
mod_fn(
data = emax_df[120:125, ],
param = new_par
)
#> [1] 9.595929 3.412750 8.208382 10.674149 1.200782 8.567196