Cómo representar funciones en R

Problema

Queremos representar funciones en R.

Solución

En nuestro ejemplo queremos representar la siguiente ecuación de segundo grado: 2x² + 20x + 3 = 0

• Opción 1: base package

f <- function(x) {
  x ^ 2 + 20 * x + 3
}
curve(expr = f, from = -100, to = 100)


• Opción 2: ggplot2

library(ggplot2)
ggplot(data.frame(x = c(-100, 100)), aes(x)) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 20 * x + 3
    }
  ) +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0)

 

Notas

Si queremos añadir más funciones:

• Opción 1: Base package

f1 <- function(x) {
  x ^ 2 + 20 * x + 3
}
f2 <- function(x) {
  x ^ 2 + 50 * x + 100
}
curve(expr = f1, from = -100, to = 100)
curve(expr = f2, from = -100, to = 100, col  = 2, add = TRUE)


• Opción 2: ggplot2

ggplot(data.frame(x = c(-100, 100)), aes(x)) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 20 * x + 3
    }
  ) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 50 * x + 100
    },
    colour = "red"
  ) +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0)
 

Entradas relacionadas

• Resolver ecuaciones de segundo grado en R

Referencias

• ggplot2 reference

How to plot functions in R

Problem

We would like to plot functions in R.

Solution

In our example we will plot the following quadratic equation: 2x² + 20x + 3 = 0

• Option 1: base package

f <- function(x) {
  x ^ 2 + 20 * x + 3
}
curve(expr = f, from = -100, to = 100)


• Option 2: ggplot2

library(ggplot2)
ggplot(data.frame(x = c(-100, 100)), aes(x)) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 20 * x + 3
    }
  ) +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0)

 

Notes

If we want to add more functions:

• Option 1: Base package

f1 <- function(x) {
  x ^ 2 + 20 * x + 3
}
f2 <- function(x) {
  x ^ 2 + 50 * x + 100
}
curve(expr = f1, from = -100, to = 100)
curve(expr = f2, from = -100, to = 100, col  = 2, add = TRUE)


• Option 2: ggplot2

ggplot(data.frame(x = c(-100, 100)), aes(x)) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 20 * x + 3
    }
  ) +
  stat_function(
    fun = function(x) {
      x ^ 2 + 50 * x + 100
    },
    colour = "red"
  ) +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0)
 

References

• ggplot2 reference

Cómo representar una curva logarítmica en R

Problema

Queremos ajustar una curva logarítmica a un diagrama de dispersión.

library(ggplot2)
ggplot(mpg, aes(displ, hwy)) +
  geom_point()

Solución

Paquete base

plot(hwy ~ displ, mpg)
logEstimate <- lm(hwy ~ log(displ), data = mpg)
curve(coef(logEstimate)[1] + coef(logEstimate)[2] * log(x), add = TRUE)

ggplot2

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  stat_smooth(method = "lm", formula = y ~ log(x))

Referencias

• stackoverflow

How to plot a log curve in R

Problem

We want to fit a logarithmic curve to a scatterplot.

library(ggplot2)
ggplot(mpg, aes(displ, hwy)) +
  geom_point()

Solution

Base package

plot(hwy ~ displ, mpg)
logEstimate <- lm(hwy ~ log(displ), data = mpg)
curve(coef(logEstimate)[1] + coef(logEstimate)[2] * log(x), add = TRUE)

ggplot2

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  stat_smooth(method = "lm", formula = y ~ log(x))

References

• stackoverflow