更新数据表中的Arima

我的问题的一个很小的版本是这样的：

我有很多时间序列

library(data.table)
library(forecast)
library(tidyverse)


 x <-arima.sim(list(order = c(1,1,0), ar = 0.7), n = 100)
 y <- arima.sim(list(order = c(1,1,0), ar = 0.1), n = 100)

data <- data.frame(x,y) %>% gather(var,value) # place into a data.frame

库（data.table）
图书馆（预测）
图书馆（tidyverse）
x我有一个解决方案，但我想知道是否有更多的R/data.table方法可以做到这一点

注意：当我正在研究解决方案时，我将数据更改为模拟ARIMA过程，以确保模型得到正确更新

解决方案：

x <-arima.sim(list(order = c(1,1,0), ar = 0.7), n = 100)
y <- arima.sim(list(order = c(1,1,0), ar = 0.1), n = 100)


data <- data.frame(x,y) %>% gather(var,value) # place into a data.frame

models <- setDT(data)[,list(model=list(auto.arima(value))), by = var]


x <-arima.sim(list(order = c(1,1,0), ar = 0.7), n = 200)
y <- arima.sim(list(order = c(1,1,0), ar = 0.1), n = 200)


data_updated <- data.frame(x,y) %>% gather(var,value) # place updated data into data.frame

data_updated <- setDT(data_updated)[, list(dat=list(value)), by = var] # turn this into lists

#Use a loop to update the models

for(i in unique(models$var)){

  models[var == paste0(i)][[1,2]] <- Arima(data_updated[var == paste0(i)][[1,2]] ,model = models[var == paste0(i)][[1,2]])

}

x
models <-setDT(data)[,list(model=list(Arima(value, model = models$model))), by = var]

x <-arima.sim(list(order = c(1,1,0), ar = 0.7), n = 100)
y <- arima.sim(list(order = c(1,1,0), ar = 0.1), n = 100)


data <- data.frame(x,y) %>% gather(var,value) # place into a data.frame

models <- setDT(data)[,list(model=list(auto.arima(value))), by = var]


x <-arima.sim(list(order = c(1,1,0), ar = 0.7), n = 200)
y <- arima.sim(list(order = c(1,1,0), ar = 0.1), n = 200)


data_updated <- data.frame(x,y) %>% gather(var,value) # place updated data into data.frame

data_updated <- setDT(data_updated)[, list(dat=list(value)), by = var] # turn this into lists

#Use a loop to update the models

for(i in unique(models$var)){

  models[var == paste0(i)][[1,2]] <- Arima(data_updated[var == paste0(i)][[1,2]] ,model = models[var == paste0(i)][[1,2]])

}