Rstan：分层多元模型的问题

我试着从这个模型的后部取样：

x是10x1向量，mu是10x1向量，sigma是10x10矩阵，psi_0是10x10矩阵，粗体1是5x1单位向量，其余是标量。在我们的分析中，F和E是两组股票的下标（我们正在进行投资组合优化）。我尝试运行以下代码：

这是模型代码，位于单独的.stan文件（finance_model.stan）中：

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有人能帮忙吗？我在网上找到的所有分层模型的示例都是单变量的，因此很难进行反向工程。

您可能会在这方面找到更具体的帮助。

data {
  int<lower=1> T;
  real k;
  real<lower=0> sigma_squared;
  real<lower=0> r_squared;
  matrix[10,10] psi;
  vector[10] x[T];
}

parameters {
  vector[10] mu_var;
  matrix[10,10] Sigma_var;
  real alpha_energy_var;
  real alpha_fin_var;
  real beta;
}

transformed parameters {
  vector[10] mu_mean;
  mu_mean = [alpha_fin_var,alpha_fin_var,alpha_fin_var,alpha_fin_var,alpha_fin_var,alpha_energy_var,alpha_energy_var,alpha_energy_var,alpha_energy_var,alpha_energy_var]';
}
model {
  target += normal_lpdf(beta | k, sqrt(r_squared));
  target += inv_wishart_lpdf(Sigma_var | 12, psi);
  target += normal_lpdf(alpha_energy_var | beta, sqrt(sigma_squared));
  target += normal_lpdf(alpha_fin_var | beta, sqrt(sigma_squared));
  target += multi_normal_lpdf(mu_var | mu_mean, Sigma_var);
  target += multi_normal_lpdf(x | mu_var,Sigma_var);
}

finance_data <- list(
  T = 574, 
  x = data_estimation,
  sigma_squared = sigma_squared,
  k = k,
  r_squared = r_squared,
  psi = psi
)

fit1 <- stan(
  file = "finance_model.stan",  # Stan program
  data = finance_data,    # named list of data
  chains = 4,             # number of Markov chains
  warmup = 1000,          # number of warmup iterations per chain
  iter = 2000,            # total number of iterations per chain
  cores = 1,              # number of cores (could use one per chain)
  refresh = 0             # no progress shown
)

[1] "Error in sampler$call_sampler(args_list[[i]]) : Initialization failed."   
[2] "Inoltre: Warning message:"                                                
[3] "In system(paste(CXX, ARGS), ignore.stdout = TRUE, ignore.stderr = TRUE) :"
[4] "  'C:/rtools40/usr/mingw_/bin/g++' not found"                             
[1] "error occurred during calling the sampler; sampling not done"