15.1: Generación de Muestras Aleatorias (Sección @ref {generar-números aleatorios})

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Aquí generaremos muestras aleatorias a partir de una serie de distribuciones diferentes y trazaremos sus histogramas.

nsamples <- 10000
nhistbins <- 100

# uniform distribution

p1 <-
  tibble(
    x = runif(nsamples)
  ) %>% 
  ggplot((aes(x))) +
  geom_histogram(bins = nhistbins) + 
  labs(title = "Uniform")

# normal distribution
p2 <-
  tibble(
    x = rnorm(nsamples)
  ) %>% 
  ggplot(aes(x)) +
  geom_histogram(bins = nhistbins) +
  labs(title = "Normal")

# Chi-squared distribution
p3 <-
  tibble(
    x = rnorm(nsamples)
  ) %>% 
  ggplot(aes(x)) +
  geom_histogram(bins = nhistbins) +
  labs(title = "Normal")

# Chi-squared distribution
p3 <-
  tibble(
    x = rchisq(nsamples, df=1)
  ) %>% 
  ggplot(aes(x)) +
  geom_histogram(bins = nhistbins) +
  labs(title = "Chi-squared")

# Poisson distribution
p4 <-
  tibble(
    x = rbinom(nsamples, 20, 0.25)
  ) %>% 
  ggplot(aes(x)) +
  geom_histogram(bins = nhistbins) +
  labs(title = "Binomial (p=0.25, 20 trials)")


plot_grid(p1, p2, p3, p4, ncol = 2)