一個因子的每個級別的自相關

Question

我想自動關聯不同級別的數據，爲每個級別生成圖。不過，我似乎無法找到一種方法，數據幀在ID的單獨拆分水平：

##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") 

任何人對如何解決這一問題，這將是偉大的任何想法！

Answer 1

你有這個奇怪的行爲，因爲變量y.var.1在你的會話中定義（也許你使用函數attach()或只是將其定義爲單獨的向量）。如果您僅在功能acf()中使用y.var.1，則會使用來自會話的此變量。您應該在acf()內部添加X$以使用定義爲數據幀data.1的一列的y.var.1。

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