AR中的ARIMA ....使用predict（）进行预测时出错

Question

data1 <- read.csv(file.choose(), header=TRUE, sep=",", dec=",")
data<-ts(data1[,2],start = c(1990,1),frequency=1)

#Plot yrs vs total cases as time series'
plot(data, xlab="Years", ylab = "Total   cases",type="o",col="blue",font.lab=2)

# Difference data to make data stationary on mean (remove trend)
plot(diff(data,lag=1),ylab="Differenced Total Cases",col="red",font.lab=2,type="o")

#log transform data to make data stationary on variance
plot(log10(data),ylab="Log (Total Cases)",col="blue",font.lab=2,type="o")

#Difference log transform data to make data stationary on both mean and variance
plot(diff(log10(data),lag=1),ylab="Differenced Log (Total Cases)",col="red",font.lab=2,type="o")

#Plot ACF and PACF to identify potential AR and MA model
par(mfrow = c(1,2))
acf(ts(diff(log10(data))),main="ACF Total Cases")
pacf(ts(diff(log10(data))),main="PACF Total Cases")

#Identification of best fit ARIMA model
ARIMAfit <- auto.arima(log10(data), approximation=FALSE,trace=FALSE)
summary(ARIMAfit)

#Forecast No. of Cases using the best fit ARIMA model
pred <- predict(ARIMAfit, n.ahead = 3)

运行包含预测函数的最后一行时出现此错误：

Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x),  : 
  'data' must be of a vector type, was 'NULL'

是因为我的数据是表格形式的吗？

以下是数据：

structure(list(Year = 1990:2012, Total.cases = c(135.146, 136.633, 156.307, 152.259, 155.899, 154.554, 179.825, 188.216, 184.277, 159.217, 177.259, 203.859, 246.246, 265.461, 245.09, 217.274, 249.885, 254.159, 242.657, 266.083, 283.69, 314.679, 326.488)), .Names = c("Year", "Total.cases"), class = "data.frame", row.names = c(NA, -23L))

Answer 1

我不清楚为什么预测并不适合您生成的ARIMA;这种方法适用于其他类似的对象，因此我怀疑它与auto.arima生成的自动调整类型有关。

无论如何，forecast包有自己的预测函数，恰当地命名为forecast：

forecast(ARIMAfit)

预测的可视化：