Устранение неисправности Rstan error «выполняется команда… имел статус 1»

Я получаю ошибку Rstan, которую я не понимаю, и эта конкретная ошибка не была рассмотрена в предыдущих вопросах.

Код R для вызова Rstan

    # Fit the model
    start = Sys.time()
    pvl_d_fit <- stan(file = 'pvl_d.stan', data = pvl_d_dat, 
              verbose = TRUE,
              warmup = 1000, iter = 4000, thin = 3, chains = 3, 
              init = 'random', pars = c(  
              "A_ind", "mu_A", "la_A",
              "w_ind", "mu_w", "la_w",
              "a_ind", "mu_a", "la_a",
              "c_ind", "mu_c", "la_c"))
    end = Sys.time()                  
    end - start 

И получите следующий результат:

SAMPLING FOR MODEL 'pvl_d' NOW (CHAIN 1).

Informational Message: The current Metropolis proposal is about to be rejected becuase of the following issue:
Error in function stan::prob::normal_log(N4stan5agrad3varE): Random variable is -1.#IND:0, but must not be nan!
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.

Кто-нибудь сталкивался с этим раньше?

(Примечание: это сообщение повторяется снова и снова).

Error in compileCode(f, code, language = language, verbose = verbose) : 
  Compilation ERROR, function(s)/method(s) not created! cygwin warning:
  MS-DOS style path detected: C:/PROGRA~1/R/R-30~1.2/etc/x64/Makeconf
  Preferred POSIX equivalent is: /cygdrive/c/PROGRA~1/R/R-30~1.2/etc/x64/Makeconf
  CYGWIN environment variable option "nodosfilewarning" turns off this warning.
  Consult the user guide for more details about POSIX paths:
    http://cygwin.com/cygwin-ug-net/using.html#using-pathnames
C:/Users/User/Documents/R/win-library/3.0/rstan/include//stansrc/stan/agrad/rev/var_stack.hpp:49:17: warning: 'void stan::agrad::free_memory()' defined but not used [-Wunused-function]
C:/Users/User/Documents/R/win-library/3.0/rstan/include//stansrc/stan/agrad/rev/chainable.hpp:87:17: warning: 'void stan::agrad::set_zero_all_adjoints()' defined but not used [-Wunused-function]
c:/rtools/gcc-4.6.3/bin/../lib/gcc/i686-w64-mingw32/4.6.3/../../../../i686-w64-mingw32/bin/as.exe: file9d8452242a.o: too many sections (39807)
C:\Users\User\AppData\Local\Temp\ccOl2E
In addition: Warning message:
running command 'C:/PROGRA~1/R/R-30~1.2/bin/x64/R CMD SHLIB file9d8452242a.cpp 2> file9d8452242a.cpp.err.txt' had status 1 

Файл stan:

    data {
      int<lower=1> n_s;                       // # subjects
      int<lower=1> n_t;                       // # trials
      int<lower=0,upper=4> choice[n_s, n_t];  // # subj. x # trials matrix with choices
      real<lower=-25,upper=2> net[n_s, n_t];  // Net amount of wins + losses   
                                              // (# subj. x # trials matrix) 
    }

    parameters {
      // Group-level mean parameters
      real mu_A_pr;   
      real mu_w_pr;
      real mu_a_pr;  
      real mu_c_pr;

      // Group-level standard deviation  
      real<lower=0> sd_A;
      real<lower=0> sd_w;
      real<lower=0> sd_a;
      real<lower=0> sd_c;    

      // Individual-level paramters    
      real A_ind_pr[n_s]; 
      real w_ind_pr[n_s]; 
      real a_ind_pr[n_s];   
      real c_ind_pr[n_s]; 
    }

    transformed parameters {
      real<lower=0,upper=1> mu_A;   
      real<lower=0,upper=5> mu_w;
      real<lower=0,upper=1> mu_a;  
      real<lower=0,upper=5> mu_c;

      // Individual-level paramters    
      real<lower=0,upper=1> A_ind[n_s]; 
      real<lower=0,upper=5> w_ind[n_s]; 
      real<lower=0,upper=1> a_ind[n_s];   
      real<lower=0,upper=5> c_ind[n_s];   

      // Group-level precision parameters  
      real<lower=0> la_A;
      real<lower=0> la_w;
      real<lower=0> la_a;
      real<lower=0> la_c;     

      mu_A <- Phi(mu_A_pr);
      mu_w <- Phi(mu_w_pr) * 5;
      mu_a <- Phi(mu_a_pr); 
      mu_c <- Phi(mu_c_pr) * 5;  

      for (s in 1:n_s)
      {
         A_ind[s] <- Phi(A_ind_pr[s]);
         w_ind[s] <- Phi(w_ind_pr[s]) * 5;
         a_ind[s] <- Phi(a_ind_pr[s]); 
         c_ind[s] <- Phi(c_ind_pr[s]) * 5;  
      }

       la_A <- pow(sd_A, -2);
       la_w <- pow(sd_w, -2);
       la_a <- pow(sd_a, -2);
       la_c <- pow(sd_c, -2);  
     }

     model {
      vector[4] p;
      real Ev[4];
      real dummy[4];
      real theta;
      real v;

      # Prior on the group-level mean parameters
      # probit scale [-Inf, Inf]  
      mu_A_pr ~ normal(0, 1);
      mu_w_pr ~ normal(0, 1);
      mu_a_pr ~ normal(0, 1);
      mu_c_pr ~ normal(0, 1);

       # Prior on the group-level standard deviation
      sd_A ~ uniform(0,1.5); 
      sd_w ~ uniform(0,1.5); 
      sd_a ~ uniform(0,1.5);    
      sd_c ~ uniform(0,1.5);

       # Individual-level paramters
       for (s in 1:n_s)
      {
        A_ind_pr[s] ~ normal(mu_A_pr, sd_A);      
        w_ind_pr[s] ~ normal(mu_w_pr, sd_w);   
        a_ind_pr[s] ~ normal(mu_a_pr, sd_a);   
        c_ind_pr[s] ~ normal(mu_c_pr, sd_c);    
      }

      for (s in 1 : n_s)  // loop over subjects
      {  
        theta <- pow(3, c_ind[s]) - 1;     

       // Trial 1
        for (d in 1 : 4)  // loop over decks
        {  
          p[d] <- .25;
          Ev[d] <- 0;
        }  
        choice[s,1] ~ categorical(p);

        // Remaining trials
        for (t in 1 : (n_t - 1))  
            { 
            if (net[s,t] >= 0)
            v <- pow(net[s,t], A_ind[s]);
            else
            v <- -1 * w_ind[s] * pow(abs(net[s,t]), A_ind[s]);

          Ev[choice[s,t]] <- (1 - a_ind[s]) * Ev[choice[s,t]] + a_ind[s] * v;      

          for (d in 1 : 4)  // loop over decks
          dummy[d] <- exp(fmax(fmin(Ev[d] * theta, 450), -450));       

          for (d in 1 : 4)  // loop over decks
          p[d] <- dummy[d] / sum(dummy); 

          choice[s, t + 1] ~ categorical(p);
        }
      } 
    }