pmx_sim | R Documentation |
Create simulation object
pmx_sim(file, data, irun, idv)
file |
|
data |
|
irun |
|
idv |
|
library(ggPMX)
theo_path <- file.path(
system.file(package = "ggPMX"), "testdata",
"theophylline"
)
WORK_DIR <- file.path(theo_path, "Monolix")
input_file <- file.path(theo_path, "data_pk.csv")
vpc_file <- file.path(theo_path, "sim.csv")
ctr <- pmx_mlx(
config = "standing",
directory = WORK_DIR,
input = input_file,
dv = "Y",
dvid = "dvid",
cats = c("SEX"),
conts = c("WT0", "AGE0"),
strats = "STUD",
settings = pmx_settings(
use.labels=TRUE,
cats.labels=list(
SEX=c("0"="Male","1"="Female")
)
),
sim = pmx_sim(
file = vpc_file,
irun ="rep",
idv="TIME"
)
)
ctr %>% pmx_plot_vpc(
strat.facet=~SEX,
facets=list(nrow=2),
type="percentile",
is.draft = FALSE,
pi = pmx_vpc_pi(interval = c(0.1,0.9),
median=list(color="green"),
extreme= list(color="green")),
obs = pmx_vpc_obs(color="blue",shape=18,size=2),
ci = pmx_vpc_ci(interval = c(0.1,0.9),
median=list(fill="pink")),
bin=pmx_vpc_bin("kmeans",n=5)
)
ctr %>%
pmx_plot_vpc(bin= pmx_vpc_bin(
style = "fixed",
fixedBreaks=c(-10,2, 5, 10,15,50))
)
# example with legend
ctr %>% pmx_plot_vpc(
is.legend = TRUE,
pi = pmx_vpc_pi(interval=c(0.02,0.98),median = list(linetype="dotted")),
ci = pmx_vpc_ci(interval = c(0.05,0.95),median=list(fill="red"))
)
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