Create a matrix of residual plots using purrr and ggplot - r

Question

Suppose I have the following dataframe:
library(tidyverse)
fit <- lm(speed ~ dist, data = cars)
select(broom::augment(fit), .fitted:.std.resid) -> dt
names(dt) <- substring(names(dt), 2)
I would like to create a grid of residuals plots using purrr. For example, I have the formulas for 2 diagnostic plots so far:
residual <- function(model) {ggplot(model, aes(fitted, resid)) +
geom_point() +
geom_hline(yintercept = 0) +
geom_smooth(se = FALSE)}
stdResidual <- function(model) {ggplot(model, aes(fitted, std.resid)) +
geom_point() +
geom_hline(yintercept = 0) +
geom_smooth(se = FALSE)}
And I am storing the formulas in a list that I plan to run against the fortified dataset dt.
formulas <- tibble(charts = list(residual, stdResidual))
# A tibble: 2 x 1
charts
<list>
1 <fun>
2 <fun>
Now I need to pass dt to each element of the column chart in formulas. I am actually also trying to combine both using gridExtra, but for now I would be satisfied if I could at least render both of them. I think I should run something like
pwalk(list(dt, formulas), ???)
But I have no idea what function I should use in ??? to render the plots.

Answer 1

Set up functions to plot each one, just like you did above:
diagplot_resid <- function(df) {
ggplot(df, aes(.fitted, .resid)) +
geom_hline(yintercept = 0) +
geom_point() +
geom_smooth(se = F) +
labs(x = "Fitted", y = "Residuals")
}
diagplot_stdres <- function(df) {
ggplot(df, aes(.fitted, sqrt(.std.resid))) +
geom_hline(yintercept = 0) +
geom_point() +
geom_smooth(se = F) +
labs(x = "Fitted", y = expression(sqrt("Standardized residuals")))
}
diagplot_qq <- function(df) {
ggplot(df, aes(sample = .std.resid)) +
geom_abline(slope = 1, intercept = 0, color = "black") +
stat_qq() +
labs(x = "Theoretical quantiles", y = "Standardized residuals")
}
Then call each in a list, with the dataframe as your second argument. Here you're invokeing a list of functions, and parallel-ly applying them to a list of function arguments. Since there's only one element to the second list, invoke_map loops over them.
fit <- lm(mpg~wt, mtcars)
df_aug <- augment(fit)
purrr::invoke_map(.f = list(diagplot_resid, diagplot_stdres, diagplot_qq),
.x = list(list(df_aug))) %>%
gridExtra::grid.arrange(grobs = ., ncol = 2,
top = paste("Diagnostic plots for",
as.expression(fit$call)))