gamssl

library(tidyverse)

# https://stats.stackexchange.com/questions/309047/zero-inflated-beta-regression-using-gamlss-for-vegetation-cover-data
# Since the data are percentages/proportions on the interval [0,1), 
# I figured a zero inflated beta regression would be appropriate. 
# I do this using the gamlss package in R:

df  <- data.frame(
    cover = c(0.0013,0,0.0208,0.0038,0,0,0,0.0043,
              0,0.002,0.0068,0.0213,0,0.0069,0.0075,0,0,0,0.013,
              0.0803,0.0328,0.1742,0,0,0.0179,0,0.3848,0.1875,0,
              0.2775,0.03,0,0.0042,0.0429),
    site = as.factor(c("A","A","A","A","A",
                       "A","A","A","A","A","A","A","A","B","B",
                       "B","B","B","B","B","C","C","C","C","C","D",
                       "D","D","D","D","D","E","E","E")))

df %>% 
  ggplot() + 
  aes(site, cover) + 
  geom_boxplot() + 
  labs(x = "Site", y = "Vegetation cover") +
  scale_y_continuous(labels = scales::percent)

library(gamlss)
library(emmeans)

m1 <- gamlss(cover ~ site,  family = BEZI, data = df, trace = F)
summary(m1)
plot(m1)

em <- emmeans(m1, "site", type = "response")
pairs(em)

library(see)

ggplot(df, 
       aes(x = site, y = cover)) +
  geom_violinhalf(flip = TRUE) +
  scale_fill_material_d()


df %>% 
  ggplot()+
  aes(x=cover, fill = site) +
  geom_density(alpha = 0.4) + 
  facet_wrap("site")