ggPMX (version 0.9.4)

residual_scatter: Scatter residual plots

Description

Scatter residual plots

DV vs PRED plot

DV vs IPRED plot

IWRES vs IPRED plot

|IWRES| vs IPRED plot

IWRES vs TIME plot

NPDE vs TIME plot

NPDE vs PRED plot

Usage

residual_scatter(point, is.hline, hline, dname, bloq, filter, strat.facet,
  facets, strat.color, trans, pmxgpar, labels, axis.title, axis.text, ranges,
  is.smooth, smooth, is.band, band, is.draft, draft, is.identity_line,
  identity_line, scale_x_log10, scale_y_log10, color.scales, ...)
pmx_plot_dv_pred(ctr, ...)
pmx_plot_dv_ipred(ctr, ...)
pmx_plot_iwres_ipred(ctr, ...)
pmx_plot_abs_iwres_ipred(ctr, ...)
pmx_plot_iwres_time(ctr, ...)
pmx_plot_npde_time(ctr, ...)
pmx_plot_npde_pred(ctr, ...)

Arguments

point

list geom_point graphical parameters.

is.hline

logical if TRUE add horizontal line y=0 ( TRUE by default).

hline

list geom_hline graphical parameters.

dname

character name of dataset to be used. User can create his own dataset using set_data and pass it as dname to be plotted.

bloq

pmxBLOQ object created by pmx_bloq.

pmx_update parameters

filter

expression filter which will be applied to plotting data.

strat.facet

formula optional stratification parameter by facetting. This split plot by strats(each strat in a facet)

facets

list facet_wrap parameters.

strat.color

character optional stratification parameter by grouping. This will split the plot by group (color) of strat.

trans

character define the transformation to apply on x or y or both variables

pmxgpar

a object of class pmx_gpar possibly the output of the

pmx_gpar: Shared basic graphics parameters

labels

list list containing plot and/or axis labels: title, subtitle, x , y

axis.title

list containing element_text attributes to customize the axis title. (similar to ggplot2 axis.title theme)

axis.text

list containing element_text attributes to customize the axis text (similar to ggplot2 axis.text theme)

ranges

list limits of x/y ranges

is.smooth

logical if set to TRUE add smooth layer

smooth

list geom_smooth graphical/smoothing fun parameters

is.band

logical if TRUE add horizontal band

band

list horizontal band parameters. geom_hline graphical parameters.

is.draft

logical if TRUE add draft layer

draft

list draft layer parameters. geom_text graphical parameters.

is.identity_line

logical if TRUE add an identity line

identity_line

listgeom_abline graphical parameters.

scale_x_log10

logical if TRUE use log10 scale for x axis.

scale_y_log10

logical if TRUE use log10 scale for y axis.

color.scales

list define scales parameter in case of strat.color pmx_settings

...

others graphics parameters passed :

• pmx_gpar internal function to customize shared graphical parameters

• residual generic object for all residual (scatter) plots .

• pmx_update function.

residual parameters

ctr

pmx controller

Value

ggplot2 object

Examples

# NOT RUN {
# NOTES ######################
# examples are availables for all residual plots:
# - pmx_plot_abs_iwres_ipred
# - pmx_plot_dv_ipred
# - pmx_plot_dv_pred
# - pmx_plot_iwres_ipred
# - pmx_plot_iwres_time
# - pmx_plot_npde_time


# basic use  ---------------------------------------

ctr <- theophylline()
p <- ctr %>% pmx_plot_dv_pred()
## p is a ggplot2 object you can add any layer here
p + ggplot2::theme_minimal()

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

## update labels
ctr %>% pmx_plot_dv_pred(
  labels = list(title = "DV versus PRED new title")
)

## remove draft
ctr %>% pmx_plot_dv_pred(is.draft = FALSE)

## remove horizontal line
ctr %>% pmx_plot_dv_pred(is.hline = FALSE)

## custom point aes and static parameters
## we can customize any geom_point parameter
ctr %>% pmx_plot_dv_pred(
  point = list(aes(alpha = DV), color = "green", shape = 4)
)



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

## continuous stratification
ctr %>% pmx_plot_dv_pred(strat.color = "WT0")
## categorical stratification
ctr %>% pmx_plot_dv_pred(strat.facet = "SEX")
## using formula notation
ctr %>% pmx_plot_dv_pred(strat.facet = STUD~SEX)

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

## we can use any expression involving the data
ctr %>% pmx_plot_dv_pred(filter = DV > mean(DV) & PRED < median(PRED))
## filter and stratify
ctr %>% pmx_plot_dv_pred(filter = SEX == 1, strat.facet = ~SEX)


# transformation  --------------------------------------

## apply a log transformation in y
ctr %>% pmx_plot_dv_pred(trans = "log10_y")
# }