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


suppose have 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 create grid of residuals plots using purrr. example, have formulas 2 diagnostic plots 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 storing formulas in list plan run against fortified dataset dt.

formulas <- tibble(charts = list(residual, stdresidual)) # tibble: 2 x 1   charts   <list> 1  <fun> 2  <fun>

now need pass dt each element of column chart in formulas. trying combine both using gridextra, satisfied if @ least render both of them. think should run like

pwalk(list(dt, formulas), ???)

but have no idea function should use in ??? render plots.

set functions plot each one, 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 list, dataframe second argument. here you're invokeing list of functions, , parallel-ly applying them list of function arguments. since there's 1 element second list, invoke_map loops on 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)))

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