【问题标题】:Error in fitting a model using auto.arima使用 auto.arima 拟合模型时出错
【发布时间】:2020-02-26 11:21:23
【问题描述】:

每当我尝试使用 auto.arima 拟合模型时,都会出现错误

auto.arima can only handle univariate time series

但我已将数据转换为时间序列。 有人可以帮忙吗?

library(forecast)
sales = data.frame(
Year = c(2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018),
Qtr1 = c(2.32,4.36,8.74,16.24,37.04,47.79,51.03,74.47,74.78,78.29,77.32),
Qtr2 = c(1.7,3.79,8.75,18.65,35.06,37.43,43.72,61.17,51.19,50.76,52.22),
Qtr3 = c(0.72,5.21,8.40,20.34,26.03,31.24,35.20,47.53,40.40,41.03,41.30),
Qtr4 = c(6.89,7.37,14.1,17.07,26.91,33.8,39.27,48.05,45.51,46.68,46.89))
sales
plot(sales)

salests = ts(sales)
tsdisplay(salests)
arima_fit = auto.arima(salests,stepwise = FALSE, approximation = FALSE) ##ERROR 

a_f = forecast(arima_fit, h =8)    
plot(a_f)

【问题讨论】:

    标签: r forecasting arima


    【解决方案1】:

    您的salests 是一个包含五个时间序列的矩阵,每列一个。第一个时间序列称为Year,然后是Qtr1Qtr4。这可能不是您想要的。

    获取您的 sales 数据,将其转换为矩阵,删除第一列(包含年份),转置它,将其转换为 vector 并将其转换为时间序列:

    salests <- ts(as.vector(t(as.matrix(sales)[,-1])),frequency=4,start=c(2008,1))
    

    【讨论】:

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