inst/examples/distribution.R

\donttest{
# *************** basic use ***************** ------

ctr <- theophylline()
## boxplot variation
p <- ctr %>% pmx_plot_eta_box()
## histogram variation
p <- ctr %>% pmx_plot_eta_hist()

# update graphical parameter  ----------------------

## add jitter
ctr %>%
  pmx_plot_eta_hist(is.jitter = TRUE, jitter = list(alpha = 0.4, color = "red"))

## remove shrinkage
ctr %>%
  pmx_plot_eta_hist(is.shrink = FALSE)

## update histogram graphical parameters
ctr %>%
  pmx_plot_eta_hist(
    histogram = list(
      color = NA,
      position = "fill",
      binwidth = 1 / 100
    )
  )



# stratification  ----------------------------------

## categorical stratification color parameter
ctr %>% pmx_plot_eta_hist(is.jitter = TRUE, strat.facet = ~STUD, strat.color = ~SEX)
  
## categorical stratification facetting
ctr %>% pmx_plot_eta_hist(strat.facet = ~SEX)

## using formula categorical stratification facetting
ctr %>% pmx_plot_eta_hist(
  strat.facet = STUD ~ SEX,
  shrink = pmx_shrink(hjust = 0.5)
)

# subsetting  --------------------------------------

## select a set of random effect
ctr %>% pmx_plot_eta_hist(filter = EFFECT %in% c("ka", "Cl"))
## filter and stratify by facets
ctr %>% pmx_plot_eta_hist(
  filter = EFFECT %in% c("ka", "Cl"), strat.facet = ~SEX
)
ctr %>% pmx_plot_eta_hist(
  filter = EFFECT %in% c("ka", "Cl"), strat.facet = ~SEX
)
}
ggPMXdevelopment/ggPMX documentation built on Dec. 11, 2023, 5:24 a.m.