r - 为面板数据中的每个组变量提取拟合值

Question

我有一个包含大量组的面板数据集。我计算了每组的拟合值，我想将所有拟合值组合到一个新的数据集中。我正在寻找一个可能的捷径来避免手动执行此操作。

以下数据集与我正在处理的数据集相似(尽管就组而言规模要小得多)。

set.seed(999)
dt <- data.frame("Group"=rep((LETTERS[1:10]), each=15),
  "Year"=2001:2015,"value"=5+rnorm(150, 3,1))
names(dt)
head(dt)
table(dt$Year, dt$Group)
library(reshape2)
dt_tbl1 <- dcast(dt,Year~Group)
dt_tbl1
library(forecast)
tsMat <- ts(dcast(dt, Year ~ Group), start=2001, freq=1)
dt_ses <- lapply(tsMat, function(x) ses(x))

我正在寻找一些帮助来自动执行以下步骤。在数据框中添加所有剩余的组。

dt_tbl2 <- data.frame("Year"=2001:2015,
data.frame(dt_ses$A$fitted),
data.frame(dt_ses$B$fitted),
data.frame(dt_ses$C$fitted))

并重命名新数据集中的变量以与原始组相关

names(dt_tbl2)[2:4] <- c("A_hat", "B_hat", "C_hat")

一旦完成，dt_tbl2 应该具有与 dt_tbl1 相同的格式。

我尝试过使用 sapply() 和 lapply() 但似乎没有任何效果。谢谢控制系统

Answer 1

dt_tbl = data.frame(Year = c(tsMat[,1]), 
                    sapply(colnames(tsMat)[-1], function(col) {dt_ses[[col]]$fitted}))

names(dt_tbl)[-1] = paste0(names(dt_tbl)[-1], "_hat")

   Year    A_hat    B_hat    C_hat    D_hat    E_hat    F_hat    G_hat    H_hat    I_hat    J_hat
1  2001 7.618084 7.521736 8.709448 7.967254 8.096049 7.932307 7.997542 7.552510 7.855070 8.136634
2  2002 7.662074 7.521647 9.150131 7.967285 8.095947 7.932320 7.997708 7.552295 7.855037 8.136680
3  2003 7.234079 7.521702 9.005576 7.967083 8.096054 7.932381 7.997711 7.552369 7.855063 8.136535
4  2004 7.919614 7.521760 8.787972 7.967088 8.096149 7.932181 7.997613 7.552552 7.854865 8.136433
5  2005 8.073512 7.521898 8.865025 7.967149 8.096250 7.932232 7.997742 7.552446 7.854703 8.136329
6  2006 7.919455 7.521738 8.572195 7.967149 8.096238 7.932222 7.997629 7.552423 7.854840 8.136423
7  2007 7.706265 7.521663 7.864789 7.967141 8.096114 7.932165 7.997734 7.552438 7.854872 8.136405
8  2008 7.010270 7.521775 7.802812 7.967079 8.095963 7.932270 7.997677 7.552331 7.854913 8.136533
9  2009 6.888603 7.521787 7.992457 7.967257 8.095926 7.932154 7.997648 7.552284 7.854947 8.136511
10 2010 6.951684 7.521864 8.130820 7.967297 8.095874 7.932169 7.997624 7.552245 7.855069 8.136587
11 2011 6.919762 7.521800 7.726980 7.967294 8.095964 7.932056 7.997646 7.552268 7.855106 8.136625
12 2012 7.976188 7.521912 7.670982 7.967325 8.095944 7.932025 7.997481 7.552206 7.855076 8.136553
13 2013 8.045479 7.521849 7.759875 7.967385 8.095928 7.932168 7.997529 7.552346 7.855074 8.136648
14 2014 8.437745 7.521808 7.485442 7.967260 8.096013 7.932149 7.997449 7.552503 7.855118 8.136644
15 2015 8.321283 7.521701 7.328202 7.967307 8.095962 7.932257 7.997381 7.552420 7.855088 8.136548