Set observation designs for the simulation
This function also allows you to assign different designs to different groups or individuals in a population.
design(x, deslist = list(), descol = character(0), ...)
x |
model object |
deslist |
a list of |
descol |
the |
... |
not used |
This setup requires the use of an idata_set, with individual-level
data passed in one ID per row. For each ID, specify a
grouping variable in idata (descol). For each unique value
of the grouping variable, make one tgrid object and pass them
in order as ... or form them into a list and pass as deslist.
You must assign the idata_set before assigning the designs in the
command chain (see the example below).
peak <- tgrid(0,6,0.1)
sparse <- tgrid(0,24,6)
des1 <- c(peak,sparse)
des2 <- tgrid(0,72,4)
data <- expand.ev(ID = 1:10, amt=c(100,300))
data$GRP <- data$amt/100
idata <- data[,c("ID", "amt")]
mod <- mrgsolve::house()
mod %>%
omat(dmat(1,1,1,1)) %>%
carry_out(GRP) %>%
idata_set(idata) %>%
design(list(des1, des2),"amt") %>%
data_set(data) %>%
mrgsim %>%
plot(RESP~time|GRP)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.