8 Poisson regression and others GLMs
8.1 Outline
library(pacman)
p_load(tidyverse, here, janitor, purrr, viridis, brms, tidybayes, bayesplot)
theme_set(theme_bw())
8.2 Poisson distribution
#df <- tibble(x = seq(from = 0, to = 20, by = 1)) %>%
# mutate(lambda_01 = dpois(x, lambda = 0.1))
#
#df %>%
# gather(key = 'key', value = 'value', -x) %>%
# separate(key, c('type', 'scale')) %>%
# mutate(scale = factor(scale, levels = sort(order(scale)))) %>%
# ggplot(aes(x = x, y = value, colour = scale)) +
# geom_line(size = 2) +
# scale_y_continuous(NULL, breaks = NULL) +
# scale_colour_viridis(discrete = TRUE) +
# labs(colour = 'Scale') +
# NULL