Error about Bernoulli and state-space model using rstan

Question

I'm trying to estimate the accuracy of the judgment for each time using the state-space model. The R code is as follows. MacOS 10.14.6, rstan 2.21.2 were used.

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

################################
#Stan
stan_model <- "
data {
  int n; //number of data
  int n_t; //number of time index
  int idx_t[n]; //index for time
  int judge[n]; //judgment
}

parameters {
  real<lower = 0, upper = 1> mu[n_t]; // mean of correct judgment
  real<lower = 0> s_mu; 
}

transformed parameters {
  real<lower = 0, upper = 1> p[n_t];
  for(i in 1 : n_t) {
    p[i] = mu[i];
  }
}


model {
  for ( i in 2 : n_t) {
    mu[i] ~ normal(mu[i - 1], s_mu);
  }
  
  for (i in 1 : n) {
    judge[i] ~ bernoulli(p[idx_t[i]]);
  }
}
"
##########################################
##########################################
d <- read.csv('./input100.csv')


d$Time_100 = d$Time * 100
d$Time_100_new = as.integer(d$Time_100)

data = data.frame(d$Time_100_new,d$judgement)
colnames(data) <- c("time","ratio")
#data

qwe = data[order(data$time),]
data = qwe

d_input <- list(n = length(data$ratio), n_t = length(sort(unique(data$time))), idx_t = data$time, judge = data$ratio)
fit <- stan(model_code = stan_model,
               data = d_input)

However, I got the error message below.

SAMPLING FOR MODEL '2cf9ed042422a42c681f58525db6a2eb' NOW (CHAIN 1).
Chain 1: Unrecoverable error evaluating the log probability at the initial value.
Chain 1: Exception: []: accessing element out of range. index 0 out of range; expecting index to be between 1 and 13; index position = 1p  (in 'model11625186b3cc5_2cf9ed042422a42c681f58525db6a2eb' at line 28)

[1] "Error in sampler$call_sampler(args_list[[i]]) : "                                                                                                                                                        
[2] "  Exception: []: accessing element out of range. index 0 out of range; expecting index to be between 1 and 13; index position = 1p  (in 'model11625186b3cc5_2cf9ed042422a42c681f58525db6a2eb' at line 28)"
error occurred during calling the sampler; sampling not done

I understood there are problems around "judge[i] ~ bernoulli(p[idx_t[i]]);", but I do not have any idea how should I do.

The input file is as follows.

Time,judgement
0,1
0.04,1
0.07,0
0.08,1
0.08,1
0.08,1
0.08,0
0.08,0
0.08,0
0.08,0
0.09,1
0.09,1
0.09,1
0.09,1
0.09,1
0.09,0
0.09,0
0.09,0
0.09,0
0.1,1
0.1,1
0.1,1
0.1,1
0.1,1
0.1,0
0.1,0
0.1,0
0.1,0
0.11,1
0.11,1
0.11,1
0.11,1
0.11,1
0.11,1
0.11,1
0.11,0
0.11,0
0.11,0
0.11,0
0.11,0
0.11,0
0.11,0
0.12,1
0.12,1
0.12,1
0.12,1
0.12,1
0.12,1
0.12,0
0.12,0
0.12,0
0.12,0
0.13,1
0.13,1
0.13,1
0.13,1
0.13,0
0.13,0
0.13,0
0.13,0
0.13,0
0.13,0
0.14,1
0.14,1
0.14,1
0.14,0
0.14,0
0.14,0
0.14,0
0.14,0
0.15,1
0.15,1
0.15,1
0.15,1
0.15,1
0.15,1
0.15,0
0.15,0
0.15,0
0.15,0
0.16,1
0.16,1
0.16,1
0.16,1
0.16,1
0.16,0
0.16,0
0.16,0
0.16,0
0.17,1
0.17,1
0.17,1
0.17,1
0.17,1
0.17,1
0.17,1
0.17,1
0.17,1
0.17,0

Answer 1

The process showed below was required.

dt_idx_time = data.table(
  time_id = sort(unique(data$time)),
  time_id_rev = 1 : length(sort(unique(data$time)))
)
vec_rev_id = dt_idx_time$time_id_rev[match(data$time, dt_idx_time$time_id)]


dt002 = data.table(
  data,
  time_rev = vec_rev_id
)

data_new = dt002