打印一组模拟 AR(1) 的系数以及 R 中的种子的优雅方法

Elegant Way to Print Coefficients of Set of Simulated AR(1) Along with there Seeds in R

我也得到了在 R and another solution to filter the true arimaorder of the simulated data that follows ARIMA(1, 0, 0) along with the seeds that produce them 中将种子自动化为向量而不是整数的解决方案。在产生指定 ARIMA 顺序的种子中,我想要 print 它们的 ar coefficients 连同那里的种子。

我试过这个:

SEED_vector <- c(14, 152, 165,528, 539, 1091, 1240, 1259, 1314, 1425, 1481, 1552)
arima_order_results = data.frame()
for (my_seed in SEED_vector){
    set.seed(my_seed)
    ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1)
    ar2 <- auto.arima(ar1, ic ="aicc")
    arr <- ar2$coef
    print(arr)
    arima_order_results = rbind(arima_order_results,arr)
}

我得到这个作为输出:

#ar1  intercept 
#-0.6920070  0.4209332 
       #ar1  intercept 
#-0.7202459 -0.3036454 
       #ar1  intercept 
#-0.8971835 -0.4130711 
      #ar1 
#0.8749406 
       #ar1 
#-0.7520381 
       #ar1  intercept 
#-0.8363416  0.3014670 
       #ar1  intercept 
#-0.7016283  0.4847039 
       #ar1  intercept 
#-0.6667556  0.6719526 
       #ar1  intercept 
#-0.6481393 -0.3125167 
       #ar1  intercept 
#-0.6084819 -0.9350262 
       #ar1  intercept 
#-0.8985071  0.4437974 
       #ar1  intercept 
#-0.7552149  1.2879873 

而不是 R 输出中的 ar1 我更喜欢产生系数

的种子数

试试这个方法:

library(forecast)
library(dplyr)
SEED_vector <- c(14, 152, 165,528, 539, 1091, 1240, 1259, 1314, 1425, 1481, 1552)
arima_order_results = data.frame()
for (my_seed in SEED_vector){
  set.seed(my_seed)
  ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1)
  ar2 <- auto.arima(ar1, ic ="aicc")
  arr <- as.data.frame(t(ar2$coef))
  arr <- cbind(data.frame(seed=my_seed),arr)
  print(arr)
  arima_order_results = bind_rows(arima_order_results,arr)
}

输出:

arima_order_results
   seed        ar1  intercept
1    14 -0.6920070  0.4209332
2   152 -0.7202459 -0.3036454
3   165 -0.8971835 -0.4130711
4   528  0.8749406         NA
5   539 -0.7520381         NA
6  1091 -0.8363416  0.3014670
7  1240 -0.7016283  0.4847039
8  1259 -0.6667556  0.6719526
9  1314 -0.6481393 -0.3125167
10 1425 -0.6084819 -0.9350262
11 1481 -0.8985071  0.4437974
12 1552 -0.7552149  1.2879873