Question

我想自动更新不同级别的数据，为每个级别生成图表。但是，我似乎无法找到一种方法来将数据帧拆分为不同的ID级别：

##My data is:
*data.1*
 ID   y.var.1
1   1  2.284620
2   1  2.820829
3   1  3.889701
4   1  5.180010
5   1  6.080572
6   2  6.972568
7   2  8.082126
8   2  9.075686
9   2  9.864694
10  2 10.942456
11  3 11.853353
12  3 13.112986
13  3 13.893405
14  3 15.037400
15  3 16.015836

## I use dlply (from the plyr package) to split the dataframe by the level ID
data_ID<-dlply(data.1, .(ID), function(X) acf(y.var.1, na.action = na.pass))
head(data_ID)

##and although this produces three groups, they all have the same values which are the same as when I do autocorrelation on the entire dataframe..
> head(data_ID)
$`1`
Autocorrelations of series ‘y.var.1’, by lag
 0      1      2      3      4      5      6      7      8      9     10     11 
 1.000  0.804  0.600  0.409  0.230  0.071 -0.075 -0.194 -0.293 -0.370 -0.409 -0.418 
$`2`
Autocorrelations of series ‘y.var.1’, by lag
 0      1      2      3      4      5      6      7      8      9     10     11 
 1.000  0.804  0.600  0.409  0.230  0.071 -0.075 -0.194 -0.293 -0.370 -0.409 -0.418 
$`3`
Autocorrelations of series ‘y.var.1’, by lag
 0      1      2      3      4      5      6      7      8      9     10     11 
 1.000  0.804  0.600  0.409  0.230  0.071 -0.075 -0.194 -0.293 -0.370 -0.409 -0.418 


> dput(data.1)
structure(list(ID = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 
3, 3), y.var.1 = c(2.28462022795481, 2.82082936729163, 3.88970139114628, 
5.18001014821836, 6.08057215599522, 6.97256785426474, 8.08212595903149, 
9.07568620628701, 9.8646935842879, 10.9424555128125, 11.8533529745958, 
13.1129856348251, 13.8934049954063, 15.0374003752388, 16.0158355330431
)), .Names = c("ID", "y.var.1"), row.names = c(NA, -15L), class = "data.frame")

任何人对如何解决这个问题都有任何想法，这很棒！

Answer 1

你有这种奇怪的行为，因为在你的会话中定义了变量y.var.1（也许你使用了函数attach()或者只是将它定义为单独的向量）。如果您只在函数y.var.1中使用acf()，则使用会话中的此变量。您应在X$内添加acf()，以使用y.var.1作为数据框data.1的一列。

 dlply(data.1, .(ID), function(X) acf(X$y.var.1, na.action = na.pass))
$`1`
Autocorrelations of series ‘X$y.var.1’, by lag   
     0      1      2      3      4 
 1.000  0.446 -0.142 -0.447 -0.357     
$`2`    
Autocorrelations of series ‘X$y.var.1’, by lag    
     0      1      2      3      4 
 1.000  0.373 -0.084 -0.373 -0.416     
$`3`    
Autocorrelations of series ‘X$y.var.1’, by lag   
     0      1      2      3      4 
 1.000  0.377 -0.086 -0.381 -0.411

Answer 2

可以使用by或tapply功能：

R > a <- by(dat$y.var.1, dat$ID, function(x) acf(x)$acf)
R > a
dat$ID: 1
, , 1

        [,1]
[1,]  1.0000
[2,]  0.4457
[3,] -0.1424
[4,] -0.4467
[5,] -0.3566

------------------------------------------------------------ 
dat$ID: 2
, , 1

         [,1]
[1,]  1.00000
[2,]  0.37311
[3,] -0.08434
[4,] -0.37320
[5,] -0.41557

------------------------------------------------------------ 
dat$ID: 3
, , 1

         [,1]
[1,]  1.00000
[2,]  0.37742
[3,] -0.08618
[4,] -0.38068
[5,] -0.41057

因子的每个层面的自相关

2 个答案: