copy of kick_model_1_1_choice.R

kick_model_1_1_choice.R

library(rstan)
library(tidyverse)

rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())

## preprocessing                     
d <- read_csv(file='Dromiidae.csv') # https://gist.github.com/kagaya/0d309397300b7e8294fe53c44b6fc525
d <- d %>%
  select(c('shell_width', 'choice',
           'id', 'leg_lack'           ))

d <- d[complete.cases(d), ]

## renumber animal id from 1
id <- as.factor(d$id)
levels(id) <- as.character(1:length(levels(id)))
d$id <- as.integer(id)

d$choice <- as.factor(d$choice)
levels(d$choice) <- c(2,1,3) # label M,L,No, as 1,2,3
d$choice <- as.integer(as.character(d$choice))

d$leg_lack <- as.factor(d$leg_lack)
levels(d$leg_lack) <- c(2,3,1) # label no_leg_lack, A, C, as 1, 2, 3
d$leg_lack <- as.integer(as.character(d$leg_lack))

data <- list(N=nrow(d), 
             K=max(d$choice),
             L=max(d$id),
             Y=d$choice,
             C_width=d$shell_width,
             Leg_lack=d$leg_lack,
             ID=d$id)

fit <- stan(file='model_1_1_choice.stan',  # kick this stan file
            data=data, seed=1234,
            chains=4, iter=6000, warmup=1000, thin=1)