inst/snippet/resid-v-fit-fig.R

In fastR2: Foundations and Applications of Statistics Using R (2nd Edition)

x <- seq(0, 10, by = 0.25) 
resid <- rnorm(length(x))
y1 <- x + resid
y2 <- (x - 5)^2 / 5 + resid
y3 <- x + (0.75 + 0.25 * x) * resid
y4 <- x + resid
y4[35] <- x[35]- 2 * max(abs(resid))
resid1 <- resid(lm(y1 ~ x))
resid2 <- resid(lm(y2 ~ x))
resid3 <- resid(lm(y3 ~ x))
resid4 <- resid(lm(y4 ~ x))
stresid1 <- resid1 / sd(resid1)
stresid2 <- resid2 / sd(resid2)
stresid3 <- resid3 / sd(resid3)
stresid4 <- resid4 / sd(resid4)
fit1 <- fitted(lm(y1 ~ x))
fit2 <- fitted(lm(y2 ~ x))
fit3 <- fitted(lm(y3 ~ x))
fit4 <- fitted(lm(y4 ~ x))
group <- rep(toupper(letters[1:4]), each = length(x))
rdata <- data.frame(
            x = rep(x, times = 4),
            fit = c(fit1, fit2, fit3, fit4),
            residual = c(resid1, resid2, resid3, resid4),
            stresidual = c(stresid1, stresid2, stresid3, stresid4),
            group = group)
gf_point(stresidual ~ fit, data = rdata) %>%
  gf_facet_wrap(~ group, scale = "free") %>%
  gf_labs(y = "residual") %>%
  gf_theme(axis.ticks = element_blank(), axis.text = element_blank())
                    # ylim = c(-1.1, 1.1) * max(abs(rdata$stresidual)),
                    # as.table = T)