我正在使用预测包和fpp2包中的某些数据。
我试图使用tsCV函数在austa时间序列上对ARIMA模型进行交叉验证。 错误之一是可疑的,可能是我可能不了解该功能的工作原理。
library(forecast)
library(fpp2)
data(austa)
farimaboxcox <- function(x, h) {
lambda <- BoxCox.lambda(x)
forecast(auto.arima(x, stepwise=FALSE, lambda = lambda), h = h)
}
e <- tsCV(austa, farimaboxcox, h = 5)
e[7:9, 4]
#[1] NA -366.4481 NA
#Try to replicate the results above
austa_training <- subset(austa, start = 1, end = 7)
austa_test <- subset(austa, start = 8, end = 12)
lambda <- BoxCox.lambda(austa_training)
fit <- forecast(auto.arima(austa_training, stepwise=FALSE, lambda = lambda), h = 5)
e <- austa_test[5] - fit$mean[5]
#[1] NA
austa_training <- subset(austa, start = 1, end = 8)
austa_test <- subset(austa, start = 9, end = 13)
lambda <- BoxCox.lambda(austa_training)
fit <- forecast(auto.arima(austa_training, stepwise=FALSE, lambda = lambda), h = 5)
e <- austa_test[5] - fit$mean[5]
#[1] NA
austa_training <- subset(austa, start = 1, end = 9)
austa_test <- subset(austa, start = 10, end = 14)
lambda <- BoxCox.lambda(austa_training)
fit <- forecast(auto.arima(austa_training, stepwise=FALSE, lambda = lambda), h = 5)
e <- austa_test[5] - fit$mean[5]
#[1] NA
为什么我从tsCV函数中收到-366.4481错误?不应该是NA吗?