Install RTools and further put its location on the environment variable PATH before installing this package. 
In addition, please update your cpp to version 1.0.9. 

install.packages("Rcpp")
library(Rcpp)
install.packages("RcppArmadillo")
library(RcppArmadillo)
install.packages("devtools")
library(devtools)
install_github("https://github.com/nanlin999/WQRADMM", force = TRUE)
library(WQRADMM)

###function for generating the correlation matrix (AR(1) or exchangeable)
gcov = function(p, rho, type){
  if(type == "exchangeable"){
    cov = matrix(rho, p, p)
    diag(cov) = rep(1, p)
  }
  else{
    cov = diag(p)
    for(i in 1:p){
      for(j in 1:p){
        if(i < j) cov[i,j] = rho^{j-i}
        else cov[i,j] = cov[j,i]
      }
    }
  }
  cov
}

###generate synthetic data (heteroscedastic model with d = 0.75*p under Student's t error)
N = 10000
p = 100
n = 10
rep = rep(n, N)
nsum = sum(rep)
d = 0.75*p
rho_X = 0.5
rho_e = 0.5
tau = 0.75
set.seed(999)
X = matrix(rnorm(nsum*p), nsum, p)
cov_X = gcov(p, rho_X, "ar1")
X = X%*%chol(cov_X)
for(i in 1:d){
  X[,i] = pnorm(X[,i])
}
set.seed(1000)
e = matrix(rt(N*n, 3), N, n)
cov_e = gcov(n, rho_e, "ar1")
e = as.vector(t(e%*%chol(cov_e)))
sigma = 0.5
e = sigma*e
beta0 = rnorm(1)
beta = rnorm(p)
Y = beta0+X%*%beta+apply(X[,1:d]*e/d, 1, sum)
beta_true = c(beta0, quantile(e/d, tau)+beta[1:d], beta[(d+1):p])

###calculate the WQR estimator by WQR-ADMM
WQR = WQRADMM(X, Y, rep, tau, intercept = TRUE, "WQR", warmstart = FALSE)
beta_WQR = WQR$Estimation_WQR
AE_WQR = sum(abs(beta_WQR-beta_true))
Time_WQR = WQR$Time_WQR
Time_WQRADMM = WQR$Time_total

###calculate the WQR estimator by parallel WQR-ADMM
k = 10              ###number of partitions
paraWQR = paraWQRADMM(X, Y, k, rep, tau, intercept = TRUE, "WQR", warmstart = FALSE)
beta_paraWQR = paraWQR$Estimation_WQR
AE_paraWQR = sum(abs(beta_paraWQR-beta_true))
Time_paraWQR = paraWQR$Time_WQR
Time_paraWQRADMM = paraWQR$Time_total

###output the results
AE_WQR              ###estimation error of WQR-ADMM            
Time_WQRADMM        ###computational time of WQR-ADMM
AE_paraWQR          ###estimation error of parallel WQR-ADMM
Time_paraWQRADMM    ###computational time of parallel WQR-ADMM