design: Set observation designs for the simulation

In mrgsolve: Simulate from ODE-Based Models

Set observation designs for the simulation

Description

This function also allows you to assign different designs to different groups or individuals in a population.

Usage

design(x, deslist = list(), descol = character(0), ...)

Arguments

x	model object
deslist	a list of tgrid or tgrids objects or numeric vector to be used in place of ...
descol	the idata column name (character) for design assignment
...	not used

Details

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).

Examples

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)

mrgsolve documentation built on Oct. 18, 2024, 5:12 p.m.