在R中多次延迟多个变量

Question

所以,我正在使用一个数据框,每天有444天的数据.我有几个变量,我想滞后用于回归模型(lm).我想每次滞后7次.我目前正在产生这样的滞后......

email_data$email_reach1 <- lag(ts(email_data$email_reach, start = 1, end = 444), 1)
email_data$email_reach2 <- lag(ts(email_data$email_reach, start = 1, end = 444), 2)
email_data$email_reach3 <- lag(ts(email_data$email_reach, start = 1, end = 444), 3)
email_data$email_reach4 <- lag(ts(email_data$email_reach, start = 1, end = 444), 4)
email_data$email_reach5 <- lag(ts(email_data$email_reach, start = 1, end = 444), 5)
email_data$email_reach6 <- lag(ts(email_data$email_reach, start = 1, end = 444), 6)
email_data$email_reach7 <- lag(ts(email_data$email_reach, start = 1, end = 444), 7)

然后,我为每个我想要滞后的变量重复这个.

这似乎是实现这一目标的可怕方式.还有更好的东西吗？

我已经考虑过滞后整个数据帧,但是我不知道如何为结果分配变量名并将其合并回原始数据帧.

Answer 1

你也可以使用data.table.(HT到@akrun)

set.seed(1)
email_data <- data.frame(dates=1:10, email_reach=rbinom(10, 10, 0.5))

library(data.table)
setDT(email_data)[, paste0('email_reach', 1:3) := shift(email_reach, 1:3)][]

#   dates email_reach email_reach1 email_reach2 email_reach3
# 1:     1           4           NA           NA           NA
# 2:     2           4            4           NA           NA
# 3:     3           5            4            4           NA
# 4:     4           7            5            4            4
# 5:     5           4            7            5            4
# 6:     6           7            4            7            5
# 7:     7           7            7            4            7
# 8:     8           6            7            7            4
# 9:     9           6            6            7            7
#10:    10           3            6            6            7

Answer 2

我认为对于任何给定的n.

n <- 7
for (i in 1:n) {
  email_data[[paste0("email_reach", i)]] <- lag(ts(email_data$email_reach, start = 1, end = 444), i)  
}