问题描述
我导入的数据包含7个变量:Y和X1，X2，X3，X4，X5，X6.我尝试在zoo中应用rollapply函数，以在具有262 obs窗口的样本内运行滚动回归. (一年中的工作日).
My imported data contains 7 variables: Y and X1, X2, X3, X4, X5, X6. I tried applying the rollapply function in zoo in order to run a rolling regression within an in-sample with a window of 262 obs. (work days in a year).
date Y X1 X2
1 10/1/07 -0.0080321720 4.690734e-03 3.333770e-03
2 10/2/07 0.0000000000 -2.818413e-03 5.418223e-03
3 10/3/07 0.0023158650 -4.178744e-03 -3.821100e-04
4 10/4/07 -0.0057491710 -5.071030e-03 -8.321550e-04
5 10/5/07 0.0073570500 3.065045e-03 5.179574e-03
6 10/8/07 0.0127708010 -7.278513e-03 1.145395e-03
7 10/9/07 0.0032661980 9.692267e-03 6.514035e-03
8 10/10/07 0.0013824430 1.161780e-04 2.676416e-03
9 10/11/07 0.0026607550 1.113179e-02 8.825719e-03
10 10/12/07 -0.0046362600 -2.453561e-03 -6.584070e-03
11 10/15/07 -0.0023757680 -7.829081e-03 -3.070540e-03
12 10/16/07 -0.0128673660 -4.619378e-03 -8.972126e-03
13 10/17/07 0.0016049760 1.276695e-03 5.349316e-03
14 10/18/07 -0.0044198970 -9.018499e-03 -1.215895e-02
15 10/19/07 -0.0011080330 -5.328661e-03 -7.131916e-03
16 10/22/07 -0.0024217970 -2.019539e-02 -2.021072e-02
17 10/23/07 0.0031270520 1.668604e-02 2.236130e-02
18 10/24/07 -0.0040367400 -1.061433e-02 -5.735703e-03
19 10/25/07 0.0001011170 1.346312e-02 1.036109e-02
20 10/26/07 0.0003032910 3.766526e-03 2.903628e-03
21 10/29/07 0.0004042450 1.416406e-02 2.527754e-03
22 10/30/07 -0.0012132240 -1.387166e-03 -8.202236e-03
23 10/31/07 0.0057497510 9.593904e-03 1.433401e-02
24 11/1/07 -0.0032238590 -1.648975e-02 -1.029199e-02
25 11/2/07 -0.0031330560 -7.737784e-03 -7.559498e-03
26 11/5/07 -0.0001012300 -7.877763e-03 -8.500554e-03
27 11/6/07 -0.0004050220 7.407770e-03 2.536320e-03
28 11/7/07 -0.0031444970 -5.904219e-03 -8.026064e-03
29 11/8/07 -0.0045822590 -3.712574e-03 -6.395584e-03
30 11/9/07 0.0016316540 -1.432552e-02 -1.741458e-02
31 11/12/07 -0.0019378860 -3.926583e-03 -4.543370e-03
32 11/13/07 0.0011223920 -1.952799e-03 -2.622112e-03
33 11/14/07 0.0008154940 8.687550e-06 1.085682e-03
34 11/15/07 0.0015272620 -1.549745e-02 -1.556172e-02
35 11/16/07 -0.0001017450 -5.578556e-03 -1.432244e-02
36 11/19/07 0.0014234880 -2.206707e-02 -3.537936e-02
37 11/20/07 -0.0010165700 1.643937e-02 5.140822e-03
38 11/21/07 -0.0008140010 -1.715961e-02 -2.756704e-02
39 11/22/07 -0.0008146640 -2.108098e-03 7.455698e-03
40 11/23/07 0.0008146640 1.266776e-02 1.615338e-02
41 11/26/07 0.0008140010 5.539814e-03 2.854080e-03
42 11/27/07 0.0006100660 -8.561106e-03 -9.720505e-03
43 11/28/07 -0.0015258640 3.392103e-02 2.132374e-02
44 11/29/07 -0.0006109980 6.109848e-03 1.045556e-02
45 11/30/07 0.0004073730 9.214342e-03 1.133690e-02
46 12/3/07 -0.0002036660 -7.006415e-03 -6.079820e-04
47 12/4/07 0.0002036660 -1.187605e-02 -2.554853e-02
48 12/5/07 0.0007125040 1.362121e-02 9.525618e-03
49 12/6/07 -0.0034655010 7.917348e-03 5.252105e-03
50 12/7/07 0.0018361730 -1.026832e-02 1.216898e-02
51 12/10/07 0.0013240310 3.347302e-03 1.143687e-02
52 12/11/07 0.0005087760 -3.433720e-03 2.373558e-03
53 12/12/07 0.0024385300 5.507930e-04 3.191504e-03
54 12/13/07 -0.0115336820 -1.793698e-02 -2.149447e-02
55 12/14/07 -0.0010271160 -2.307745e-03 -1.038483e-03
56 12/17/07 -0.0033969870 -1.822079e-02 -2.920662e-02
57 12/18/07 0.0000000000 -1.873297e-03 -7.061215e-03
58 12/19/07 -0.0004125410 -3.372400e-06 -7.879850e-03
59 12/20/07 0.0008249120 -6.227957e-03 -1.752460e-04
60 12/21/07 -0.0020635580 1.734991e-02 1.348190e-02
61 12/24/07 0.0003098050 0.000000e+00 0.000000e+00
62 12/25/07 0.0000000000 0.000000e+00 0.000000e+00
63 12/26/07 0.0001032470 0.000000e+00 0.000000e+00
64 12/27/07 0.0006192590 5.006783e-03 5.274480e-03
65 12/28/07 -0.0005160230 6.428153e-03 8.557260e-03
66 12/31/07 0.0000000000 0.000000e+00 0.000000e+00
67 1/1/08 0.0002064410 0.000000e+00 0.000000e+00
68 1/2/08 -0.0009293200 -6.023384e-03 -3.104400e-03
69 1/3/08 0.0027853730 -2.302511e-03 -2.759650e-03
70 1/4/08 0.0018526150 -2.149450e-02 -2.645257e-02
71 1/7/08 -0.0005142710 -4.445206e-03 -2.117698e-
1596 <NA> <NA> <NA>
由于某些原因，最后一行没有显示值，即使原始excel文件中也没有(X3，X4，X5，X6丢失，因为各列相互堆叠，我复制了该示例从顶部开始进行批处理.
the last line for some reason doesn't show the values,even though there are in the original excel file(X3,X4,X5,X6 are missing,since the columns are stacked on top of each other,I copied the batch from the top for the example.
我的代码是:
rollapply(ts, 262, lm(
Y~X1+X2+X3+X4+X5+X6+0, subset=1:floor(length(x)/2)),
align="right")
我收到的错误消息是:
Error in eval(expr, envir, enclos) : object 'Y' not found
我真的很奇怪为什么找不到Y变量，因为它以适当的标题显示在时间序列数据集中.
I really wonder why it can not find the Y variable, since it is displayed in the time series dataset with the appropriate heading.
推荐答案
目前尚不清楚您的数据实际上是什么(使用dput(example_data)给出可重复的示例).
It is not really clear what your data actually is (use dput(example_data) to give reproducible examples).
但是您的示例中的lm调用只是一次又一次地进行相同的回归(您的x不变)，并且正如josilber指出的那样，它应该是一个函数.这是一个示例，其中所有数据都在data.frame allRegData中，并且至少有两列，一列名为y，另一列名为x:
But the lm call in your example is simply doing the same regression over and over again (your x is not changing) and as josilber points out, it is supposed to be a function. Here is an example where all the data is in the data.frame allRegData and it has at least two columns, one named y and another named x:
require(zoo)
rollapply(zoo(allRegData),
width=262,
FUN = function(Z)
{
t = lm(formula=y~x, data = as.data.frame(Z), na.rm=T);
return(t$coef)
},
by.column=FALSE, align="right")
这篇关于R中使用roll apply的滚动回归的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！