Script based ‘NONMEM’ model development in RStudio intended for intermediate to advanced R users.
You can install the released version of NMproject from CRAN with:
To install the latest version of NMproject from GitHub:
if(!require("devtools")) install.packages("devtools") devtools::install_github("tsahota/NMproject")
To install a specific release (e.g. v0.5.1) on GitHub use the following command:
Load the package with
Use of pipes,
%>%, make it easy to code sequences of operations to
Following snippet adds covariates to model object,
m2WT <- m2 %>% child(run_id = "m2WT") %>% add_cov(param = "CL", cov = "WT", state = "power") %>% run_nm()
Graphical RStudio ‘Addins’ exist for reviewing the changes that
add_cov() make before execution and performing
For more complex operations use fully tracked manual edits.
Apply fully customisable diagnostic reports to one or multiple objects
nm_render() like so:
c(m1, m2) %>% nm_render("Scripts/basic_gof.Rmd") ## Saves html diagnostic reports in "Results" directory
Scripts/basic_gof.Rmd can also be run as an R notebook
for interactively customising to your specific model evaluation
Here’s a snippet for producing PPCs and VPCs:
m2s <- m2 %>% child(run_id = "m2s") %>% update_parameters(m2) %>% convert_to_simulation(subpr = 50) %>% run_nm() m2s %>% nm_render("Scripts/basic_vpc.Rmd") m2s %>% nm_render("Scripts/basic_ppc.Rmd")
Advanced functionality enables groups of runs to be handled with the same concise syntax (no loops). For example:
m1rep <- m1 %>% child(run_id = 1:5) %>% init_theta(init = rnorm(init, mean = init, sd = 0.3)) %>% init_omega(init = runif(init, min = init/2, max = init*2)) %>% run_in("Models/m1_perturb_inits") %>% run_nm()
See the website vignette for more examples
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