This function performs model predictions based on the provided model and dose specifications
Usage
# S3 method for class 'modelFits'
predict(object, doses = NULL, ...)
Examples
posterior_list <- list(Ctrl = RBesT::mixnorm(comp1 = c(w = 1, m = 0, s = 1), sigma = 2),
DG_1 = RBesT::mixnorm(comp1 = c(w = 1, m = 3, s = 1.2), sigma = 2),
DG_2 = RBesT::mixnorm(comp1 = c(w = 1, m = 4, s = 1.5), sigma = 2) ,
DG_3 = RBesT::mixnorm(comp1 = c(w = 1, m = 6, s = 1.2), sigma = 2) ,
DG_4 = RBesT::mixnorm(comp1 = c(w = 1, m = 6.5, s = 1.1), sigma = 2))
models <- c("emax", "exponential", "sigEmax", "linear")
dose_levels <- c(0, 1, 2, 4, 8)
fit <- getModelFits(models = models,
posterior = posterior_list,
dose_levels = dose_levels)
predict(fit, doses = c(0, 1, 3, 4, 6, 8))
#> $emax
#> [1] -0.008147777 2.977266585 5.136083687 5.647278697 6.271281080
#> [6] 6.637935274
#>
#> $exponential
#> [1] 1.636554 2.207315 3.461645 4.150114 5.663125 7.377590
#>
#> $sigEmax
#> [1] 0.00731386 2.89049046 5.22947029 5.72787171 6.28978958 6.59200716
#>
#> $linear
#> [1] 1.419597 2.167297 3.662695 4.410394 5.905792 7.401191
#>
#> attr(,"doses")
#> [1] 0 1 3 4 6 8