tutoria3a

library(tidyverse)

## ── Attaching packages ───────────────────────────────────────────── tidyverse 1.3.0 ──

## ✓ ggplot2 3.3.2     ✓ purrr   0.3.4
## ✓ tibble  3.0.3     ✓ dplyr   1.0.1
## ✓ tidyr   1.1.1     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.5.0

## ── Conflicts ──────────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(broom)
library(palmerpenguins)
library(MASS)

## 
## Attaching package: 'MASS'

## The following object is masked from 'package:dplyr':
## 
##     select

df <- tibble(x = 1:20, y = c(1:18, 49:50))

ggplot(df, aes(x, y)) + 
  geom_point(size = 2) + theme_bw(base_size = 12)

fit_lm <- lm(y ~ x, data = df) 
fit_rlm <- rlm(y ~ x, data = df) 


augment.rlm <- function(fit, ...) {
   broom:::augment.rlm(fit) %>% 
    mutate(w = fit$w)
}
dfa <- augment(fit_rlm) 

ggplot(dfa, aes(x, y, color = w)) + 
  geom_point(size = 2) + 
  geom_smooth(method = "lm", se = FALSE, color = "#C8008F") +
  geom_smooth(method = "rlm", se = FALSE, color = "#027EB6") + 
  annotate("text", x = 20.5, y = c(21, 31), 
           label = c("rlm", "lm")) + 
  theme_bw(base_size = 12) + 
  labs(title = "Robust vs. non-robust linear models") + 
  scale_color_continuous(type = "viridis")