geom_quantile

Fits a quantile regression to the data and draws the fitted quantiles with lines and then converts them with ggplotly

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
p <-  m + geom_quantile()

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ x

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
p <-  m + geom_quantile(quantiles = 0.5)

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ x

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
q10 <- seq(0.05, 0.95, by = 0.05)
p <-  m + geom_quantile(quantiles = q10)

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ x

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
p <-  m + geom_quantile(method = "rqss")

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ qss(x, lambda = 1)

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
p <-  m + geom_quantile(method = "rqss", lambda = 0.1)

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ qss(x, lambda = 0.1)

m <-
  ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point()
p <-  m + geom_quantile(colour = "red", size = 2, alpha = 0.5)

plotly::ggplotly(p)

## Smoothing formula not specified. Using: y ~ x

GGPLOT - geom_quantile