Residual Plots

Kyle Baron

2020-06-30

Set up

library(pmplots)
library(dplyr)

data <- pmplots_data_obs()

Residuals versus time

res_time(data)

## `geom_smooth()` using formula 'y ~ x'

wres_time(data)

## `geom_smooth()` using formula 'y ~ x'

cwresi_time(data)

## `geom_smooth()` using formula 'y ~ x'

cwresi_tad(data, xby = 24)

## `geom_smooth()` using formula 'y ~ x'

Residuals versus PRED

res_pred(data)

## `geom_smooth()` using formula 'y ~ x'

wres_pred(data)

## `geom_smooth()` using formula 'y ~ x'

cwresi_pred(data)

## `geom_smooth()` using formula 'y ~ x'

Residual histogram

cwresi_hist(data)

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Residual QQ plot

cwresi_q(data)

Residuals versus categorical variable

wres_cat(data, x  = "STUDYc//Study")

Residuals versus continuous variables

cwresi_cont(data, x= "WT//Weight (kg)")

## `geom_smooth()` using formula 'y ~ x'