This is a dummy blog posts

This is a test post. In this post, I try out different functionalities

Heading 1

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Merriweather

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3 - Code

This is inline code plus a small code chunk.

library(tidyverse)
ggplot(mpg) +
  geom_jitter(aes(cty, hwy), size = 4, alpha = 0.5) 

3 - Tabsets

Transforming OLS estimates

Code

preds_lm %>% 
  ggplot(aes(body_mass_g, bill_length_mm, col = correct)) +
  geom_jitter(size = 4, alpha = 0.6) +
  facet_wrap(vars(species)) +
  scale_color_manual(values = c('grey60', thematic::okabe_ito(3)[3])) +
  scale_x_continuous(breaks = seq(3000, 6000, 1000)) +
  theme_minimal(base_size = 12) +
  theme(
    legend.position = 'top', 
    panel.background = element_rect(color = 'black'),
    panel.grid.minor = element_blank()
  ) +
  labs(
    x = 'Body mass (in g)',
    y = 'Bill length (in mm)'
  )

Maximizing likelihood

Code

glm.mod <- glm(sex ~ body_mass_g + bill_length_mm + species, family = binomial, data = dat)
preds <- dat %>% 
  mutate(
    prob.fit = glm.mod$fitted.values,
    prediction = if_else(prob.fit > 0.5, 'male', 'female'),
    correct = if_else(sex == prediction, 'correct', 'incorrect')
  )
preds %>% 
  ggplot(aes(body_mass_g, bill_length_mm, col = correct)) +
  geom_jitter(size = 4, alpha = 0.6) +
  facet_wrap(vars(species)) +
  scale_x_continuous(breaks = seq(3000, 6000, 1000)) +
  scale_color_manual(values = c('grey60', thematic::okabe_ito(3)[3])) +
  theme_minimal(base_size = 10) +
  theme(
    legend.position = 'top', 
    panel.background = element_rect(color = 'black'),
    panel.grid.minor = element_blank()
  ) +
  labs(
    x = 'Body mass (in g)',
    y = 'Bill length (in mm)'
  )

4 - Some math stuff

\[ \int_0^1 f(x) \ dx \]

2 - Columns

geom_density(
  mapping = NULL,
  data = NULL,
  stat = "density",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  outline.type = "upper"
)

stat_density(
  mapping = NULL,
  data = NULL,
  geom = "area",
  position = "stack",
  ...,
  bw = "nrd0",
  adjust = 1,
  kernel = "gaussian",
  n = 512,
  trim = FALSE,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

2 - Margin captions

ggplot(data = gapminder::gapminder, mapping = aes(x = lifeExp, fill = continent)) +
  stat_density(position = "identity", alpha = 0.5)

Bla bla bla. This is a caption in the margin. Super cool isn’t it?