构造一个“简单”的固定滚动窗口

Question

是否有可能建立一个“简单”的固定滚动窗口？说我有以下数据集：

         Apple Microsoft     Tesla    Amazon
 2010 0.8533719 0.8078440 0.2620114 0.1869552
 2011 0.7462573 0.5127501 0.5452448 0.1369686
 2012 0.7580671 0.5062639 0.7847919 0.8362821
 2013 0.3154078 0.6960258 0.7303597 0.6057027
 2014 0.4741735 0.3906580 0.4515726 0.1396147
 2015 0.4230036 0.4728911 0.1262413 0.7495193
 2016 0.2396552 0.5001825 0.6732861 0.8535837
 2017 0.2007575 0.8875209 0.5086837 0.2211072
#I want to be able to produce the following result
s.matrix <- x[1:4,] 
#For the next period, I want to drop the first period and add the next period: 
s.matrix <- x[2:5,] 
#For the rest of the dataset it should be:
 x[3:6,], x[4:7,], x[5:8,]
#That is, the width should always be equal to four. 

我知道lapply能够做同样的事情，但后来我不得不设置一个固定值，它只是增加了新的变数已经存在的矩阵，而不除去第一观察....还是我错了？

Answer 1

假设x是data.frame如在端部的笔记，用rollapply以获得所需的索引和apply以产生数据帧的相应列表。

library(zoo)

apply(rollapply(1:nrow(x), 4, c), 1, function(ix) x[ix, ])

赠送：

[[1]]
       Apple Microsoft   Tesla  Amazon
2010 0.85337   0.80784 0.26201 0.18696
2011 0.74626   0.51275 0.54524 0.13697
2012 0.75807   0.50626 0.78479 0.83628
2013 0.31541   0.69603 0.73036 0.60570

[[2]]
       Apple Microsoft   Tesla  Amazon
2011 0.74626   0.51275 0.54524 0.13697
2012 0.75807   0.50626 0.78479 0.83628
2013 0.31541   0.69603 0.73036 0.60570
2014 0.47417   0.39066 0.45157 0.13961

[[3]]
       Apple Microsoft   Tesla  Amazon
2012 0.75807   0.50626 0.78479 0.83628
2013 0.31541   0.69603 0.73036 0.60570
2014 0.47417   0.39066 0.45157 0.13961
2015 0.42300   0.47289 0.12624 0.74952

[[4]]
       Apple Microsoft   Tesla  Amazon
2013 0.31541   0.69603 0.73036 0.60570
2014 0.47417   0.39066 0.45157 0.13961
2015 0.42300   0.47289 0.12624 0.74952
2016 0.23966   0.50018 0.67329 0.85358

[[5]]
       Apple Microsoft   Tesla  Amazon
2014 0.47417   0.39066 0.45157 0.13961
2015 0.42300   0.47289 0.12624 0.74952
2016 0.23966   0.50018 0.67329 0.85358
2017 0.20076   0.88752 0.50868 0.22111

注意

我们用它进行x：

Lines <- "         Apple Microsoft     Tesla    Amazon
 2010 0.8533719 0.8078440 0.2620114 0.1869552
 2011 0.7462573 0.5127501 0.5452448 0.1369686
 2012 0.7580671 0.5062639 0.7847919 0.8362821
 2013 0.3154078 0.6960258 0.7303597 0.6057027
 2014 0.4741735 0.3906580 0.4515726 0.1396147
 2015 0.4230036 0.4728911 0.1262413 0.7495193
 2016 0.2396552 0.5001825 0.6732861 0.8535837
 2017 0.2007575 0.8875209 0.5086837 0.2211072"

x <- read.table(text = Lines)