r 中单个数据帧中的当前和未来预测

Question

我在下面有一个数据集，我想对其进行线性回归，然后在单个数据框中获取它们的拟合值和上限和下限。

该数据集包含每个国家和地区组合的五周数据。 即对于 US 和 G 组合线性回归 model 将在其中数量将在五周内按周回归，然后此 model 将用于预测 6 周。 我的最终数据框看起来像这样

我所做的是一种组合

data <- data.frame(country = c("US","US","US","US","US","US","US","US","US","US","UK","UK","UK","UK","UK"),
               Area = c("G","G","G","G","G","I","I","I","I","I","A","A","A","A","A"),
               week = c(1,2,3,4,5,1,2,3,4,5,1,2,3,4,5),amount = c(12,23,34,32,12,12,34,45,65,45,45,34,23,43,43))

data_1 <- data[(data$country=="US" & data$Area=="G"),]
# model building on initial five weeks
model <- lm(amount ~ week, data = data_1)


# creating one future week: week no 6
future <- data.frame(country="US",Area="G",week=6,amount = NA)
data2 <- rbind(data_1,future)

# prediction on all 6 weeks
pre <- predict(model,newdata = data2,interval = "prediction",level = 0.95)
pre

我从这里得到提示Looping linear regression output in a data frame in r

但无法复制这一点以包括所有其他组合的第 6 周预测。 请帮忙！

Answer 1

我主要是复制你的应对，最后只是结合结果的问题

data_1 <- data[(data$country=="US" & data$Area=="G"),]
# model building on initial five weeks
model <- lm(amount ~ week, data = data_1)
pre1 <- predict(model,newdata = data_1, interval = "prediction",level = 0.95)

# creating one future week: week no 6
future <- data.frame(country="US",Area="G",week=6,amount = NA)
data_2 <- rbind(data_1,future)

# prediction on all 6 weeks
pre2 <- predict(model,newdata = data_2, interval = "prediction",level = 0.95)

rbind(
  cbind(data_1,pre1),
  cbind(data_2,pre2)
)

   country Area week amount  fit       lwr      upr
1       US    G    1     12 20.8 -27.67915 69.27915
2       US    G    2     23 21.7 -21.99851 65.39851
3       US    G    3     34 22.6 -19.38417 64.58417
4       US    G    4     32 23.5 -20.19851 67.19851
5       US    G    5     12 24.4 -24.07915 72.87915
11      US    G    1     12 20.8 -27.67915 69.27915
21      US    G    2     23 21.7 -21.99851 65.39851
31      US    G    3     34 22.6 -19.38417 64.58417
41      US    G    4     32 23.5 -20.19851 67.19851
51      US    G    5     12 24.4 -24.07915 72.87915
6       US    G    6     NA 25.3 -30.23984 80.83984