Debug some stan code

my_example.R

# load libraries
library(purrr)
library(tidyverse)

# positive_round function 
positive_round <- function(...) round(pmax(..., 0), 0)

# adstock function
adstock<-function(x,rate=0){
  return(as.numeric(stats::filter(x=x,filter=rate,method="recursive")))
}

my_adstock <- function(x, rate){
  y <- NULL
  my_vector <- vector("numeric")
  for(i in seq(x)) {
    
       # Adstock: y[i] = x[i] + f[1]*y[i-1] + … + f[p]*y[i-p]
       y[1] <- x[i]
       y[i + 1] <- x[i + 1] + rate * y[i + 1 - 1]
       # store as vector
       my_vector[i] <- y[i]
  }
  # return results of vector
  my_vector
}

# base and ad constants 
base     <-  100 
n_weeks  <-  104
avg      <-  20
sdev     <-  10 

# adstock rates
ad1_rate <- .7
ad2_rate <- .4
ad3_rate <- .5

set.seed(42)
# 3 ads with mean
fake_df <- rep(avg, 3) %>%
  # normal distribution with 2 years of observations
  map(~ rnorm(n = n_weeks, mean = .x, sd = sdev)) %>% 
  # make sure there are no 0s and make values integers
  map(~ positive_round(0,.x)) %>% 
  # convert lists to data frame
  map_dfc(~as_tibble(.x)) %>% 
  # sensible names
  setNames(c("ad1", "ad2", "ad3")) %>% 
  # sales = sum of adstock and some noise
  mutate(sales = base + 
           adstock(ad1, ad1_rate) + 
           adstock(ad2, ad2_rate) + 
           adstock(ad3, ad3_rate) +
           rnorm(n(), sd = 5)) %>% 
  # round sales to whole number
  mutate(sales =  round(sales, 0))

library(brms)



prior1 <- prior(normal(.5, .5), nlpar = "ad1rate") + 
          prior(normal(.5, .5), nlpar = "ad2rate") +
          prior(normal(.5, .5), nlpar = "ad3rate") +
          prior(normal(1, .5), nlpar = "b1") +
          prior(normal(1, .5), nlpar = "b2") +
          prior(normal(1, .5), nlpar = "b3") +
          prior(normal(100, 50), nlpar = "basesales") 
  
my_stan_adstock <- "
  vector my_stan_adstock(vector x, real rate, int N){
  vector[N] y;
  vector[N] my_vector;
      for(i in 1:N){ 
       y[0] = x[i];
       y[i] = x[i] + rate * y[i - 1];
       my_vector[i] = y[i];
     }
  return my_vector;
  }
"
  
fit1 <- brm(bf(sales ~ basesales + 
                 b1 * my_stan_adstock(ad1, ad1rate, 104) + 
                 b2 * my_stan_adstock(ad2, ad2rate, 104) + 
                 b3 * my_stan_adstock(ad3, ad3rate, 104), 
               basesales + b1 + b2 + b3 + ad1rate + ad2rate + ad3rate ~ 1, 
               nl = TRUE),
            stan_funs = my_stan_adstock,
            data = fake_df, 
            prior = prior1)