循环计算并将 auto.arima()
和 forecast()
结果存储在 Dataframe 中
可以使用以下命令生成包含随机数据的数据帧的小样本
df <- data.frame(col1 = runif(24, 400, 700),
col2 = runif(24, 350, 600),
col3 = runif(24, 600, 940),
col4 = runif(24, 2000, 2600),
col5 = runif(24, 950, 1200))
colnames(df) <- c("NorthHampton to EastHartford", "NorthHampton to Edison",
"NorthHampton to Yonkers", "North Hampton to Brooklyn", "NorthHampton to Rotterdam" )
我尝试在 R 中使用 auto.arima()
运行一系列 ARIMA
模型,但很难以所需的格式生成输出。下面是我开始的示例部分。
ts <- ts(df, frequency = 12, start = c(2014, 1), end = c(2015, 12))
model <- list()
results <- list()
for (i in 1:ncol(ts)) {
fit <- auto.arima(ts[,i], stepwise = F, approximation = F)
model <- forecast(fit)$method
results <- forecast(fit, h = 3)$mean
# print(forecast(fit)$method)
# print(forecast(fit, h=3)$mean)
}
理想情况下,我希望我的循环填充一个 data.frame
,其格式如下:
Lane Model Time PointEstimate
Northampton to East Hartford "ARIMA(0,0,0) with non-zero mean" Jan-16
Northampton to East Hartford "ARIMA(0,0,0) with non-zero mean" Feb-16
Northampton to East Hartford "ARIMA(0,0,0) with non-zero mean" Mar-16
Northampton to Edison "ARIMA(0,0,0) with non-zero mean" Jan-16
Northampton to Edison "ARIMA(0,0,0) with non-zero mean" Feb-16
Northampton to Edison "ARIMA(0,0,0) with non-zero mean" Mar-16
Northampton to Yonkers "ARIMA(0,0,0) with non-zero mean" Jan-16
列Lane
的结果应与原始数据帧中的列名称相同。 Model
的结果是 forecast(fit)$method
的结果,点估计应该是 forecast(fit, h = 3) 的结果$mean
,在本例中,每个项目在 dataframe
中重复 h 次
(3)。
我认为我的循环正在执行我需要的计算,我只是不知道如何存储结果,然后将结果附加到循环末尾的下一次迭代。我很感激我能得到的任何帮助。
最佳答案
您可以尝试以下方法:
library(forecast)
fits <- lapply(1:ncol(ts), function(i) auto.arima(ts[,i], stepwise = F, approximation = F))
models <- sapply(1:ncol(ts), function(i) forecast(fits[[i]])$method)
results <- lapply(1:ncol(ts), function(i) forecast(fits[[i]], h = 3)$mean)
resultsdf <- data.frame(do.call(rbind, results))
colnames(resultsdf) <- format(as.Date(time(results[[1]])), "%b-%y")
resultsdf$Lane=colnames(df)
resultsdf$Model=models
library(reshape2)
res <- melt(resultsdf, id.vars=4:5, measure.vars=1:3, variable;name = "Time",value;name = "PointEstimate")
Lane Model variable value
1 NorthHampton to EastHartford ARIMA(0,0,0) with non-zero mean janv.-16 546.9441
2 NorthHampton to Edison ARIMA(0,0,0) with non-zero mean janv.-16 487.6225
3 NorthHampton to Yonkers ARIMA(0,0,0) with non-zero mean janv.-16 778.9514
4 North Hampton to Brooklyn ARIMA(1,0,0) with non-zero mean janv.-16 2459.3983
5 NorthHampton to Rotterdam ARIMA(1,0,0) with non-zero mean janv.-16 1098.1912
6 NorthHampton to EastHartford ARIMA(0,0,0) with non-zero mean févr.-16 546.9441
7 NorthHampton to Edison ARIMA(0,0,0) with non-zero mean févr.-16 487.6225
8 NorthHampton to Yonkers ARIMA(0,0,0) with non-zero mean févr.-16 778.9514
9 North Hampton to Brooklyn ARIMA(1,0,0) with non-zero mean févr.-16 2416.4848
10 NorthHampton to Rotterdam ARIMA(1,0,0) with non-zero mean févr.-16 1077.3921
11 NorthHampton to EastHartford ARIMA(0,0,0) with non-zero mean mars-16 546.9441
12 NorthHampton to Edison ARIMA(0,0,0) with non-zero mean mars-16 487.6225
13 NorthHampton to Yonkers ARIMA(0,0,0) with non-zero mean mars-16 778.9514
14 North Hampton to Brooklyn ARIMA(1,0,0) with non-zero mean mars-16 2397.1000
15 NorthHampton to Rotterdam ARIMA(1,0,0) with non-zero mean mars-16 1085.3332
关于r - 将预测结果合并到 R 中的内聚数据框架中,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/35661709/