I wanted to try beta binominal to see if it helps with the high dispersion in my data. I had just been using beta distribution in brms. I did just like the vignette and it was able to run the model

```
beta_binomial2 <- custom_family(
"beta_binomial2", dpars = c("mu", "phi"),
links = c("logit", "log"), lb = c(NA, 0),
type = "int", vars = "vint1[n]"
)
stan_funs <- "
real beta_binomial2_lpmf(int y, real mu, real phi, int T) {
return beta_binomial_lpmf(y | T, mu * phi, (1 - mu) * phi);
}
int beta_binomial2_rng(real mu, real phi, int T) {
return beta_binomial_rng(T, mu * phi, (1 - mu) * phi);
}
"
stanvars <- stanvar(scode = stan_funs, block = "functions")
brmbetabin = brm(incurrent | vint(consumed) ~ Region+food+genus +Region:food + Region:genus + genus:food + (1|sample), family = beta_binomial2, data = REdata, stanvars = stanvars)
```

however I was getting errors

```
SAMPLING FOR MODEL '56e4d552c3161029f952436f8350b609' NOW (CHAIN 1).
Chain 1: Rejecting initial value:
Chain 1: Log probability evaluates to log(0), i.e. negative infinity.
Chain 1: Stan can't start sampling from this initial value.
```

I would like to just use the percentage data so I tried to change it so I took out the vint1 from the code and I changed it a couple of times and kept getting different errors in how it was written

```
beta_binomial2 <- custom_family(
"beta_binomial2", dpars = c("mu", "phi"),
links = c("logit", "log"), lb = c(NA, 0),
type = "real"
)
stan_funs <- "
real beta_binomial2_lpmf(int y, real mu, real phi, real T) {
return beta_binomial_lpmf(y | T, mu * phi, (1 - mu) * phi);
}
int beta_binomial2_rng(real mu, real phi, int T) {
return beta_binomial_rng(T, mu * phi, (1 - mu) * phi);
}
"
stanvars <- stanvar(scode = stan_funs, block = "functions")
brmbetabin = brm(Redecimal ~ Region+food+genus +Region:food + Region:genus + genus:food + (1|sample), family = beta_binomial2, data = REdata, stanvars = stanvars)
```

I get different errors for the stan_funs code about the lmpf or rng

```
SYNTAX ERROR, MESSAGE(S) FROM PARSER:
No matches for:
beta_binomial_lpmf(int, real, real, real)
Available argument signatures for beta_binomial_lpmf:
beta_binomial_lpmf(int, int, real, real)
beta_binomial_lpmf(int, int, real, real[ ])
beta_binomial_lpmf(int, int, real, vector)
beta_binomial_lpmf(int, int, real, row_vector)
beta_binomial_lpmf(int, int, real[ ], real)
beta_binomial_lpmf(int, int, real[ ], real[ ])
beta_binomial_lpmf(int, int, real[ ], vector)
```

or

```
SYNTAX ERROR, MESSAGE(S) FROM PARSER:
No matches for:
beta_binomial2_lpmf(int, real, real)
Available argument signatures for beta_binomial2_lpmf:
beta_binomial2_lpmf(int, real, real, int)
error in 'model59b436405ba8_file59b4ba57408' at line 65, column 54
-------------------------------------------------
63: if (!prior_only) {
64: for (n in 1:N) {
65: target += beta_binomial2_lpmf(Y[n] | mu[n], phi);
^
66: }
-------------------------------------------------
```

I tried different switches from continuous to discrete data but have been unable to get it to run. I am new to coding and running models so any help with the rejecting of initial values error or how to modify the custom family properly to get the model to run. I am saying that my data is continuous because they they come from large count values. I have consumed food particles out of total incurrent food particles and I made them into a percentage of retention efficiency.

- Operating System: Windows 10
- brms Version: 2.12.0

thanks