我试图根据3个变量预测税基（时间序列）：减税，收入流入和经济利润。
我尝试将auto.arima与xreg一起使用，但我收到错误：
找不到合适的ARIMA模型。
从2011年到2013年，减税数据基本上都是零，2014年是50,000，2015年是75,000，接下来的几年是10万。 此外，减税就像每家公司获得100,000美元的第一笔100,000美元利润一样免税。我真的想知道我的模型是正确的，否则我应该如何建模这些数据？代码如下：
tb = ts(data1$Taxbreak, start = c(2001), frequency = 1)
inflows = ts(data1$`Inflow of earnings`, start = c(2001), frequency = 1)
ep = ts(data1$`Economic Profits`, start = c(2001), frequency = 1)
xreg = cbind(tb, inflows,ep)
colnames(xreg) <- c("taxbreak","inflows", "economic profit")
xreg
B =ts(data1$`GR Tax Base`, start = c(2001), frequency = 1)
Box.test(B, lag = 15, type = "Ljung-Box")#stationary
acf(B)
revfit<-auto.arima(B, xreg=xreg)
tsdisplay(residuals(revfit))
newtb = ts(forecasted1$Taxbreak, start = c(2017), frequency = 1)
newinflows = ts(forecasted1$`Inflow of earnings`, start = c(2017), frequency = 1)
newperep = ts(forecasted1$`Economic Profits`, start = c(2017), frequency = 1)
nnewxreg = cbind(newtb, newinflows, newep)
nnewxreg
fcast <- forecast(revfit, xreg = nnewxreg)
list(fcast)
plot(fcast)
tsdisplay(residuals(fcast))
accuracy(fcast)
这是我用来访问
的数据revfit<-auto.arima(B, xreg=xreg)
tsdisplay(residuals(revfit))
我在这一步得到了错误。
Year Taxbreak earnings Profits Tax Base
2001 $0.00 $5,332,463 762 32,222,803,774
2002 $0.00 $5,431,753 808 33,610,875,248
2003 $0.00 $5,643,742 979 30,835,183,333
2004 $0.00 $6,134,432 1,179 36,383,352,174
2005 $0.00 $6,433,098 1,375 48,219,466,667
2006 $0.00 $6,871,455 1,578 59,596,984,211
2007 $0.00 $7,265,704 1,609 60,346,996,997
2008 $0.00 $7,390,580 1,435 61,060,551,948
2009 $0.00 $7,171,789 1,237 64,854,063,604
2010 $0.00 $7,258,068 1,588 60,502,826,855
2011 $0.00 $7,581,240 1,782 61,554,035,336
2012 $0.00 $7,862,034 1,952 68,020,593,640
2013 $0.00 $7,903,139 2,006 75,653,752,650
2014 $1.00 $8,211,705 2,026 77,369,017,668
2015 $1.00 $8,625,298 2,098 73,887,957,597
2016 $1.00 9095703 2288.857 76,386,659,364
对于其余的代码，我计划使用以下数据作为我的newxreg来预测2017年至2020年的税基
Year Taxbreak earnings Profits
2017 $1.00 9330906 2,384
2018 $1.00 9566108 2,497
2019 $1.00 9801311 2,575
2020 $1.00 10036513 2,670
2021 $1.00 10271716 2,766
2022 $1.00 10506918 2,861