> 循环周期 <- 600
> 季回归 <- 培训数据$闭市价 %>% 
        matrix(dimnames = list(培训数据$年月日时分, '闭市价')) %>% 
        tk_ts(frequency = 循环周期)
      rownames(季回归) <- 培训数据$年月日时分
> 季回归
Time Series:
Start = c(1, 1) 
End = c(2, 600) 
Frequency = 600 
            闭市价
1451592060 120.208
1451592120 120.208
1451592180 120.208
1451592240 120.208
1451592300 120.208
1451592360 120.208
1451592420 120.208
1451592480 120.208
1451592540 120.208
1451592600 120.208
1451592660 120.208
1451592720 120.208
1451592780 120.208
1451592840 120.208
1451592900 120.208
1451592960 120.208
1451593020 120.208
1451593080 120.208
1451593140 120.208
1451593200 120.208
1451593260 120.208
1451593320 120.208
1451593380 120.208
1451593440 120.208
1451593500 120.208
1451593560 120.208
1451593620 120.208
1451593680 120.208
1451593740 120.208
1451593800 120.208
1451593860 120.208
1451593920 120.208
1451593980 120.208
1451594040 120.208
1451594100 120.208
1451594160 120.208
1451594220 120.208
1451594280 120.208
1451594340 120.208
1451594400 120.208
1451594460 120.208
1451594520 120.208
1451594580 120.208
1451594640 120.208
1451594700 120.208
1451594760 120.208
1451594820 120.208
1451594880 120.208
1451594940 120.208
1451595000 120.208
1451595060 120.208
1451595120 120.208
1451595180 120.208
1451595240 120.208
1451595300 120.208
1451595360 120.208
1451595420 120.208
1451595480 120.208
1451595540 120.208
1451595600 120.208
1451595660 120.208
1451595720 120.208
1451595780 120.208
1451595840 120.208
1451595900 120.208
1451595960 120.208
1451596020 120.208
1451596080 120.208
1451596140 120.208
1451596200 120.208
1451596260 120.208
1451596320 120.208
1451596380 120.208
1451596440 120.208
1451596500 120.208
1451596560 120.208
1451596620 120.208
1451596680 120.208
1451596740 120.208
1451596800 120.208
1451596860 120.208
1451596920 120.208
1451596980 120.208
1451597040 120.208
1451597100 120.208
1451597160 120.208
1451597220 120.208
1451597280 120.208
1451597340 120.208
1451597400 120.208
1451597460 120.208
1451597520 120.208
1451597580 120.208
1451597640 120.208
1451597700 120.208
1451597760 120.208
1451597820 120.208
1451597880 120.208
1451597940 120.208
1451598000 120.208
 [ reached getOption("max.print") -- omitted 1100 rows ]

Tried to build ts format seasonal dataset and forecast::Arima() but all errors, somebody take a look?

> Arima(季回归)
Error in solve.default(res$hessian * n.used, A) : 
  Lapack routine dgesv: system is exactly singular: U[1,1] = 0
> Arima(季回归, order = c(3, 1, 0))
Error in optim(init[mask], armaCSS, method = optim.method, hessian = FALSE,  : 
  initial value in 'vmmin' is not finite
> Arima(季回归, order = c(2, 1, 0))
Error in optim(init[mask], armaCSS, method = optim.method, hessian = FALSE,  : 
  initial value in 'vmmin' is not finite
> Arima(季回归, order = c(2, 0, 0))
Error in stats::arima(x = x, order = order, seasonal = seasonal, include.mean = include.mean,  : 
  non-stationary AR part from CSS
> Arima(季回归, order = c(1, 0, 0))
Error in stats::arima(x = x, order = order, seasonal = seasonal, include.mean = include.mean,  : 
  non-stationary AR part from CSS
> Arima(季回归, order = c(0, 0, 0))
Error in solve.default(res$hessian * n.used, A) : 
  Lapack routine dgesv: system is exactly singular: U[1,1] = 0
> Arima(季回归, order = c(1, 1, 1))
Error in optim(init[mask], armaCSS, method = optim.method, hessian = FALSE,  : 
  initial value in 'vmmin' is not finite
> Arima(季回归, order = c(0, 1, 1))
Error in optim(init[mask], armaCSS, method = optim.method, hessian = FALSE,  : 
  initial value in 'vmmin' is not finite
> Arima(季回归, order = c(0, 0, 1))
Error in solve.default(res$hessian * n.used, A) : 
  system is computationally singular: reciprocal condition number = 4.19528e-25

Citation : robjhyndman/forecast#910 (comment)