我正在使用“plm”功能通过以下代码运行面板回归:
test_reg=plm(y~x1+x2+x3+x4*x7+x5*x7+x6*x7+x8+x9+x10+x11,DATA, index = c("year","id"),model ="within")
summary(test_reg)
然后我得到以下错误:
Error in names(y) <- namesy :
'names' attribute [343] must be the same length as the vector [0]
但是，当我切换y变量和x10变量并再次运行相同的'plm'函数时，我没有得到这样的错误，它的工作原理如下:
test_reg=plm(x10~x1+x2+x3+x4*x7+x5*x7+x6*x7+x8+x9+y+x11,DATA, index = c("year","id"),model ="within")
summary(test_reg)
数据如下所示:
Date ID x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y x11
01/01/2017 1 1 0 0 1 0 0 1 6.5 291.7261837 0.003809784 -0.002609372 0.06258402
01/01/2017 2 0 0 0 1 0 0 1 6.5 291.7261837 0.003809784 -0.002609372 0.06258402
01/01/2017 3 1 0 0 0 1 0 0 7.8 291.7261837 0.005244375 -0.002609372 0.06258402
01/03/2017 4 1 0 0 0 0 0 0 7.8 291.7261837 0.006340987 -0.002609372 0.06258402
01/04/2017 5 0 0 0 1 0 0 1 6.5 291.7261837 0.003923172 0.105154594 0.062638589
01/04/2017 6 0 0 0 1 0 0 1 6.5 291.7261837 0.003923172 0.105154594 0.062638589
01/04/2017 7 0 1 0 1 0 0 0 6.5 291.7261837 0.010499933 0.105154594 0.062638589
01/04/2017 8 0 0 0 0 1 0 0 7.3 291.7261837 0.004619899 0.105154594 0.062638589
01/05/2017 9 0 0 0 0 1 0 0 6.1 291.7261837 0.0069687 -0.16129731 0.062806962
01/05/2017 10 0 0 0 1 0 0 0 7.7 291.7261837 0.006392705 -0.16129731 0.062806962
01/05/2017 11 0 0 0 0 1 0 0 7.3 291.7261837 0.003693392 -0.16129731 0.062806962
01/06/2017 12 1 0 0 1 0 0 1 6.5 291.7261837 0.003951792 -0.070975051 0.06281527
01/06/2017 13 0 1 0 1 0 0 0 6.3 291.7261837 0.006345245 -0.070975051 0.06281527
01/06/2017 14 0 1 0 1 0 0 0 7.8 291.7261837 0.006057317 -0.070975051 0.06281527
01/06/2017 15 0 0 0 0 0 0 0 3.2 291.7261837 0.017651031 -0.070975051 0.06281527
01/07/2017 16 0 1 0 1 0 0 1 6.5 291.7261837 0.003230524 -0.003762958 0.062785401
01/07/2017 17 0 0 0 1 0 0 1 6.5 291.7261837 0.003230524 -0.003762958 0.062785401
01/08/2017 18 0 0 0 1 0 0 1 6.5 291.7261837 0.003575814 -0.003762958 0.062785401
01/09/2017 19 0 0 0 1 0 0 1 6.5 291.7261837 0.003751772 -0.003762958 0.062785401
01/09/2017 20 0 0 0 1 0 0 1 6.5 291.7261837 0.003751772 -0.003762958 0.062785401
01/10/2017 21 0 0 0 1 0 0 1 6.5 291.7261837 0.003236778 0.010738193 0.062756344
01/10/2017 22 1 0 0 0 0 0 0 6.3 291.7261837 0.005293044 0.010738193 0.062756344
01/11/2017 23 0 0 0 1 0 0 1 6.5 291.7261837 0.002724046 -0.159969555 0.062920422
01/11/2017 24 0 0 0 1 0 0 1 6.5 291.7261837 0.002724046 -0.159969555 0.062920422
01/11/2017 25 0 0 0 1 0 0 0 5.8 291.7261837 0.004853874 -0.159969555 0.062920422
01/11/2017 26 0 0 0 0 1 0 0 6.3 291.7261837 0.006511518 -0.159969555 0.062920422
01/12/2017 27 0 1 0 1 0 0 1 6.5 291.7261837 0.002594988 0.046721689 0.062906992
01/12/2017 28 0 1 0 1 0 0 0 7.3 291.7261837 0.003968837 0.046721689 0.062906992
01/13/2017 29 0 0 0 1 0 0 1 6.5 291.7261837 0.002472768 0.028186561 0.062883091
01/13/2017 30 0 0 0 1 0 0 0 6.1 291.7261837 0.007287802 0.028186561 0.062883091
01/13/2017 31 1 0 0 0 0 0 0 6.3 291.7261837 0.004395253 0.028186561 0.062883091
01/13/2017 32 1 0 0 0 0 0 0 6.3 291.7261837 0.004395253 0.028186561 0.062883091
01/13/2017 33 0 0 0 1 0 0 0 7.8 291.7261837 0.00674419 0.028186561 0.062883091
01/14/2017 34 0 0 0 1 0 0 1 6.5 291.7261837 0.002287315 0.003937596 0.062853342
01/14/2017 35 0 0 0 1 0 0 1 6.5 291.7261837 0.002287315 0.003937596 0.062853342
01/14/2017 36 1 0 0 0 0 0 0 3.2 291.7261837 0.016146024 0.003937596 0.062853342
01/15/2017 37 0 1 0 1 0 0 1 6.5 291.7261837 0.002474269 0.003937596 0.062853342
01/15/2017 38 0 0 1 1 0 0 0 7.3 291.7261837 0.005575788 0.003937596 0.062853342
01/16/2017 39 0 0 0 1 0 0 1 6.5 291.7261837 0.002719306 0.003937596 0.062853342
01/16/2017 40 0 0 0 0 1 0 0 7.3 291.7261837 0.008550097 0.003937596 0.062853342
01/16/2017 41 0 1 0 1 0 0 0 5.7 291.7261837 0.006760413 0.003937596 0.062853342
01/17/2017 42 0 1 0 1 0 0 1 6.5 291.7261837 0.002718686 0.078898669 0.062870506
01/17/2017 43 0 1 0 1 0 0 0 5.7 291.7261837 0.006016846 0.078898669 0.062870506
01/17/2017 44 0 0 0 1 0 0 0 7.3 291.7261837 0.005614425 0.078898669 0.062870506
01/17/2017 45 0 0 0 1 0 0 0 5.7 291.7261837 0.004262791 0.078898669 0.062870506
01/18/2017 46 0 0 0 1 0 0 1 6.5 291.7261837 0.002472575 -0.028161673 0.062846684
01/18/2017 47 0 1 0 1 0 0 1 6.5 291.7261837 0.002472575 -0.028161673 0.062846684
01/18/2017 48 0 1 0 1 0 0 1 6.5 291.7261837 0.002472575 -0.028161673 0.062846684
01/20/2017 49 0 0 0 1 0 0 1 6.5 291.7261837 0.002401105 -0.006736635 0.062794741
01/20/2017 50 0 0 0 1 0 0 1 6.5 291.7261837 0.002401105 -0.006736635 0.062794741
01/20/2017 51 0 1 0 1 0 0 1 6.5 291.7261837 0.002401105 -0.006736635 0.062794741
01/20/2017 52 0 0 0 1 0 0 1 6.5 291.7261837 0.002401105 -0.006736635 0.062794741
01/21/2017 53 0 1 0 1 0 0 1 6.5 291.7261837 0.002553359 0.024072255 0.062769421
01/21/2017 54 0 0 0 1 0 0 0 7.3 291.7261837 0.005116216 0.024072255 0.062769421
01/21/2017 55 0 1 0 1 0 0 0 7.8 291.7261837 0.006584331 0.024072255 0.062769421
01/22/2017 56 0 1 0 1 0 0 1 6.5 291.7261837 0.002955839 0.024072255 0.062769421
01/23/2017 57 0 0 0 1 0 0 0 6.5 291.7261837 0.015364925 0.024072255 0.062769421
01/23/2017 58 0 0 0 0 0 1 0 5.2 291.7261837 0.004840524 0.024072255 0.062769421
01/23/2017 59 0 0 1 1 0 0 0 7.8 291.7261837 0.007814092 0.024072255 0.062769421
01/24/2017 60 0 1 0 1 0 0 1 6.5 291.7261837 0.003216472 -0.012183546 0.062740895
01/24/2017 61 0 0 0 1 0 0 1 6.5 291.7261837 0.003216472 -0.012183546 0.062740895
01/25/2017 62 0 0 0 1 0 0 1 6.5 291.7261837 0.003073038 -0.018516248 0.062713872
01/25/2017 63 0 0 0 1 0 0 1 6.5 291.7261837 0.003073038 -0.018516248 0.062713872
01/25/2017 64 0 1 0 1 0 0 1 6.5 291.7261837 0.003073038 -0.018516248 0.062713872
01/25/2017 65 0 0 0 1 0 0 1 6.5 291.7261837 0.003073038 -0.018516248 0.062713872
01/25/2017 66 0 0 0 1 0 0 1 6.5 291.7261837 0.003073038 -0.018516248 0.062713872
01/25/2017 67 0 1 0 1 0 0 0 4.3 291.7261837 0.006130505 -0.018516248 0.062713872
01/25/2017 68 0 1 0 1 0 0 0 7.3 291.7261837 0.005463339 -0.018516248 0.062713872
01/25/2017 69 0 0 0 0 1 0 0 7.2 291.7261837 0.005378501 -0.018516248 0.062713872
01/25/2017 70 0 1 0 0 1 0 0 7.8 291.7261837 0.006395996 -0.018516248 0.062713872
01/26/2017 71 0 0 0 1 0 0 1 6.5 291.7261837 0.003005659 0.025344647 0.06268914
01/26/2017 72 0 0 0 1 0 0 1 6.5 291.7261837 0.003005659 0.025344647 0.06268914
01/26/2017 73 0 1 0 1 0 0 0 8.3 291.7261837 0.005294032 0.025344647 0.06268914
01/27/2017 74 0 0 0 1 0 0 1 6.5 291.7261837 0.003009194 0.004480483 0.062659769
01/27/2017 75 0 1 0 1 0 0 1 6.5 291.7261837 0.003009194 0.004480483 0.062659769
01/27/2017 76 1 0 0 1 0 0 0 5.7 291.7261837 0.005807761 0.004480483 0.062659769
01/27/2017 77 0 0 0 0 1 0 0 6.1 291.7261837 0.006862177 0.004480483 0.062659769
02/01/2017 78 0 0 1 1 0 0 0 6.5 225.4411382 0.011340764 0.017358588 0.062584951
02/02/2017 79 1 0 0 1 0 0 1 6.5 225.4411382 0.002466055 0.026781623 0.062560967
02/02/2017 80 0 1 0 0 1 0 0 5.7 225.4411382 0.007882781 0.026781623 0.062560967
02/03/2017 81 0 0 0 1 0 0 1 6.5 225.4411382 0.002405885 0.011539691 0.062532642
02/03/2017 82 1 0 0 0 1 0 0 7.2 225.4411382 0.005045113 0.011539691 0.062532642
02/03/2017 83 1 0 0 1 0 0 0 7.8 225.4411382 0.003676336 0.011539691 0.062532642
02/04/2017 84 0 0 0 1 0 0 1 6.5 225.4411382 0.002654186 0.010467481 0.06250418
02/04/2017 85 0 1 0 1 0 0 0 6.1 225.4411382 0.006578092 0.010467481 0.06250418
02/04/2017 86 0 1 0 1 0 0 0 7.8 225.4411382 0.003632123 0.010467481 0.06250418
02/05/2017 87 0 0 0 1 0 0 0 7.3 225.4411382 0.005081024 0.010467481 0.06250418
02/06/2017 88 0 0 0 0 0 0 1 6.5 225.4411382 0.003728276 0.010467481 0.06250418
02/06/2017 89 0 0 0 1 0 0 1 6.5 225.4411382 0.003728276 0.010467481 0.06250418
02/06/2017 90 0 1 0 1 0 0 1 6.5 225.4411382 0.003728276 0.010467481 0.06250418
02/06/2017 91 0 0 0 1 0 0 0 6.1 225.4411382 0.007556925 0.010467481 0.06250418
02/07/2017 92 1 0 0 0 1 0 0 6.1 225.4411382 0.00669479 0.025720122 0.062479891
02/07/2017 93 1 0 0 0 0 0 0 6.3 225.4411382 0.005333849 0.025720122 0.062479891
02/07/2017 94 0 0 0 1 0 0 0 5.7 225.4411382 0.005515754 0.025720122 0.062479891
02/07/2017 95 0 1 0 1 0 0 0 7.7 225.4411382 0.00544694 0.025720122 0.062479891
02/07/2017 96 1 0 0 0 0 0 0 7.3 225.4411382 0.004661699 0.025720122 0.062479891
02/07/2017 97 0 0 0 0 0 0 0 7.8 225.4411382 0.003527638 0.025720122 0.062479891
02/08/2017 98 0 1 0 1 0 0 1 6.5 225.4411382 0.00317671 0.009337221 0.06245134
02/08/2017 99 0 1 0 1 0 0 1 6.5 225.4411382 0.00317671 0.009337221 0.06245134
02/08/2017 100 0 0 0 1 0 0 0 6.1 225.4411382 0.00590983 0.009337221 0.06245134
02/08/2017 101 0 1 0 1 0 0 0 7.8 225.4411382 0.002880073 0.009337221 0.06245134
02/08/2017 102 0 0 0 1 0 0 0 7.8 225.4411382 0.002880073 0.009337221 0.06245134
02/09/2017 103 0 1 0 1 0 0 1 6.5 225.4411382 0.003220582 -0.073642932 0.062462725
02/09/2017 104 0 1 0 1 0 0 0 7.7 225.4411382 0.00457101 -0.073642932 0.062462725
02/09/2017 105 0 1 0 1 0 0 0 7.3 225.4411382 0.006184487 -0.073642932 0.062462725
02/09/2017 106 1 0 0 0 1 0 0 6.7 225.4411382 0.007553324 -0.073642932 0.062462725
02/10/2017 107 1 0 0 1 0 0 1 6.5 225.4411382 0.003220913 0.02054262 0.062436737
02/10/2017 108 0 1 0 0 1 0 0 7.3 225.4411382 0.006192293 0.02054262 0.062436737
02/10/2017 109 1 0 0 0 1 0 0 6.3 225.4411382 0.005740194 0.02054262 0.062436737
02/11/2017 110 0 0 0 0 1 0 0 5.8 225.4411382 0.005764743 -0.005847667 0.062407891
02/12/2017 111 1 0 0 0 0 1 0 7.8 225.4411382 0.002921387 -0.005847667 0.062407891
02/13/2017 112 0 0 1 1 0 0 0 6.1 225.4411382 0.007966682 -0.005847667 0.062407891
02/14/2017 113 1 0 0 1 0 0 1 6.5 225.4411382 0.00347653 0.014188136 0.062380333
02/14/2017 114 0 0 0 1 0 0 1 6.5 225.4411382 0.00347653 0.014188136 0.062380333
02/14/2017 115 0 0 0 1 0 0 1 6.5 225.4411382 0.00347653 0.014188136 0.062380333
02/14/2017 116 0 0 0 0 1 0 0 6.1 225.4411382 0.007354973 0.014188136 0.062380333
02/14/2017 117 0 1 0 1 0 0 0 4.3 225.4411382 0.005106887 0.014188136 0.062380333
02/14/2017 118 0 0 0 0 0 1 0 6.5 225.4411382 0.00458087 0.014188136 0.062380333
02/14/2017 119 0 0 0 0 1 0 0 4.5 225.4411382 0.004021296 0.014188136 0.062380333
02/15/2017 120 0 1 0 0 1 0 1 6.5 225.4411382 0.003084593 -0.000418977 0.062351313
02/15/2017 121 0 0 0 1 0 0 0 6.1 225.4411382 0.006590897 -0.000418977 0.062351313
02/15/2017 122 1 0 0 1 0 0 0 7.7 225.4411382 0.004885155 -0.000418977 0.062351313
02/15/2017 123 0 0 0 1 0 0 0 5.2 225.4411382 0.0040034 -0.000418977 0.062351313
02/15/2017 124 1 0 0 0 0 1 0 5.3 225.4411382 0.004399054 -0.000418977 0.062351313
02/16/2017 125 0 0 0 0 1 0 0 7.3 225.4411382 0.004595518 0.022443541 0.062326088
02/17/2017 126 1 0 0 1 0 0 1 6.5 225.4411382 0.002695262 0.022801391 0.062301021
02/17/2017 127 0 0 0 1 0 0 1 6.5 225.4411382 0.002695262 0.022801391 0.062301021
02/18/2017 128 0 0 0 1 0 0 1 6.5 225.4411382 0.002666188 0.005619794 0.062272353
02/19/2017 129 0 0 0 1 0 0 1 6.5 225.4411382 0.002879882 0.005619794 0.062272353
02/19/2017 130 0 1 0 0 0 0 0 7.3 225.4411382 0.005188592 0.005619794 0.062272353
02/20/2017 131 0 1 0 1 0 0 1 6.5 225.4411382 0.003248565 0.005619794 0.062272353
02/21/2017 132 0 1 0 0 1 0 0 6.1 225.4411382 0.007379637 0.048719839 0.062261158
02/22/2017 133 0 0 0 1 0 0 1 6.5 225.4411382 0.002943242 0.013892505 0.062233763
02/22/2017 134 0 0 0 1 0 0 1 6.5 225.4411382 0.002943242 0.013892505 0.062233763
02/22/2017 135 0 0 1 1 0 0 0 6.1 225.4411382 0.006542636 0.013892505 0.062233763
02/22/2017 136 1 0 0 0 0 1 0 6.3 225.4411382 0.003502356 0.013892505 0.062233763
02/23/2017 137 0 1 0 1 0 0 1 6.5 225.4411382 0.002936277 0.019675489 0.062207849
02/23/2017 138 1 0 0 0 1 0 0 7.3 225.4411382 0.005512353 0.019675489 0.062207849
02/24/2017 139 0 0 0 1 0 0 0 6.1 225.4411382 0.006400431 0.018114563 0.062181535
02/24/2017 140 0 0 0 1 0 0 0 6.1 225.4411382 0.006400431 0.018114563 0.062181535
02/25/2017 141 0 1 0 1 0 0 1 6.5 225.4411382 0.002827164 0.014374927 0.062154355
02/25/2017 142 0 0 0 1 0 0 0 7.8 225.4411382 0.002229686 0.014374927 0.062154355
02/27/2017 143 0 1 0 1 0 0 1 6.5 225.4411382 0.003494087 0.014374927 0.062154355
02/27/2017 144 0 0 0 1 0 0 0 6.1 225.4411382 0.008110374 0.014374927 0.062154355
02/27/2017 145 0 0 0 0 1 0 0 6.3 225.4411382 0.008688621 0.014374927 0.062154355
02/27/2017 146 1 0 0 1 0 0 0 4.5 225.4411382 0.013588313 0.014374927 0.062154355
02/27/2017 147 1 0 0 0 1 0 0 5.3 225.4411382 0.004551333 0.014374927 0.062154355
02/28/2017 148 0 1 0 1 0 0 1 6.5 225.4411382 0.003137535 -0.00217941 0.062125715
02/28/2017 149 1 0 0 0 1 0 0 8.3 225.4411382 0.004169185 -0.00217941 0.062125715
03/01/2017 150 0 0 0 1 0 0 1 6.5 238.161619 0.002826907 0.024337051 0.062101474
03/01/2017 151 0 0 0 1 0 0 1 6.5 238.161619 0.002826907 0.024337051 0.062101474
03/01/2017 152 0 0 0 1 0 0 1 6.5 238.161619 0.002826907 0.024337051 0.062101474
03/01/2017 153 0 0 0 1 0 0 0 6.1 238.161619 0.007100868 0.024337051 0.062101474
03/01/2017 154 0 0 0 1 0 0 0 6.1 238.161619 0.007100868 0.024337051 0.062101474
03/01/2017 155 0 0 0 1 0 0 0 6.1 238.161619 0.007100868 0.024337051 0.062101474
03/01/2017 156 0 0 0 1 0 0 0 7.8 238.161619 0.00321752 0.024337051 0.062101474
03/01/2017 157 0 0 0 1 0 0 0 7.8 238.161619 0.00321752 0.024337051 0.062101474
03/01/2017 158 0 0 0 1 0 0 0 7.8 238.161619 0.00321752 0.024337051 0.062101474
03/02/2017 159 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 160 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 161 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 162 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 163 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 164 0 0 0 1 0 0 1 6.5 238.161619 0.003262569 0.049481385 0.062091033
03/02/2017 165 0 1 0 1 0 0 0 7.3 238.161619 0.005423948 0.049481385 0.062091033
03/02/2017 166 0 1 0 1 0 0 0 7.3 238.161619 0.005423948 0.049481385 0.062091033
03/02/2017 167 0 1 0 1 0 0 0 7.3 238.161619 0.005423948 0.049481385 0.062091033
03/03/2017 168 1 0 0 1 0 0 1 6.5 238.161619 0.003261096 -0.004402012 0.062062609
03/03/2017 169 1 0 0 1 0 0 1 6.5 238.161619 0.003261096 -0.004402012 0.062062609
03/03/2017 170 1 0 0 1 0 0 1 6.5 238.161619 0.003261096 -0.004402012 0.062062609
03/04/2017 171 0 0 0 1 0 0 0 5.8 238.161619 0.009462591 0.001234096 0.062034093
03/04/2017 172 0 0 0 1 0 0 0 5.8 238.161619 0.009462591 0.001234096 0.062034093
03/04/2017 173 0 0 0 1 0 0 0 5.8 238.161619 0.009462591 0.001234096 0.062034093
03/06/2017 174 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 175 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 176 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 177 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 178 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 179 0 0 0 1 0 0 1 6.5 238.161619 0.003904071 0.001234096 0.062034093
03/06/2017 180 0 0 0 1 0 0 0 6.1 238.161619 0.008682166 0.001234096 0.062034093
03/06/2017 181 0 0 0 1 0 0 0 6.1 238.161619 0.008682166 0.001234096 0.062034093
03/06/2017 182 0 0 0 1 0 0 0 6.1 238.161619 0.008682166 0.001234096 0.062034093
03/07/2017 183 0 1 0 1 0 0 1 6.5 238.161619 0.003368821 -0.018231974 0.062008065
03/07/2017 184 0 1 0 1 0 0 1 6.5 238.161619 0.003368821 -0.018231974 0.062008065
03/07/2017 185 0 1 0 1 0 0 1 6.5 238.161619 0.003368821 -0.018231974 0.062008065
03/08/2017 186 1 0 0 1 0 0 0 6.1 238.161619 0.006993576 -0.055975584 0.0620028
03/08/2017 187 1 0 0 1 0 0 0 6.1 238.161619 0.006993576 -0.055975584 0.0620028
03/08/2017 188 1 0 0 1 0 0 0 6.1 238.161619 0.006993576 -0.055975584 0.0620028
03/09/2017 189 0 0 0 1 0 0 0 5.7 238.161619 0.00637861 0.010374975 0.061975174
03/09/2017 190 0 0 0 1 0 0 0 5.7 238.161619 0.00637861 0.010374975 0.061975174
03/09/2017 191 0 0 0 1 0 0 0 5.7 238.161619 0.00637861 0.010374975 0.061975174
03/09/2017 192 0 1 0 1 0 0 0 6.3 238.161619 0.006919775 0.010374975 0.061975174
03/09/2017 193 0 1 0 1 0 0 0 6.3 238.161619 0.006919775 0.010374975 0.061975174
03/09/2017 194 0 1 0 1 0 0 0 6.3 238.161619 0.006919775 0.010374975 0.061975174
03/10/2017 195 0 1 0 1 0 0 0 6.7 238.161619 0.005170876 -0.086404737 0.062001949
03/10/2017 196 0 1 0 1 0 0 0 6.7 238.161619 0.005170876 -0.086404737 0.062001949
03/10/2017 197 0 1 0 1 0 0 0 6.7 238.161619 0.005170876 -0.086404737 0.062001949
03/11/2017 198 0 0 0 1 0 0 0 6.8 238.161619 0.004537821 0.120279563 0.062080276
03/11/2017 199 0 0 0 1 0 0 0 6.8 238.161619 0.004537821 0.120279563 0.062080276
03/11/2017 200 0 0 0 1 0 0 0 6.8 238.161619 0.004537821 0.120279563 0.062080276
03/11/2017 201 0 0 0 0 0 0 0 5.7 238.161619 0.004403423 0.120279563 0.062080276
03/11/2017 202 0 0 0 0 0 0 0 5.7 238.161619 0.004403423 0.120279563 0.062080276
03/11/2017 203 0 0 0 0 0 0 0 5.7 238.161619 0.004403423 0.120279563 0.062080276
03/12/2017 204 0 1 0 0 0 0 1 6.5 238.161619 0.002966075 0.120279563 0.062080276
03/12/2017 205 0 1 0 0 0 0 1 6.5 238.161619 0.002966075 0.120279563 0.062080276
03/12/2017 206 0 1 0 0 0 0 1 6.5 238.161619 0.002966075 0.120279563 0.062080276
03/13/2017 207 0 0 0 1 0 0 0 6.1 238.161619 0.008535417 0.120279563 0.062080276
03/13/2017 208 0 0 0 1 0 0 0 6.1 238.161619 0.008535417 0.120279563 0.062080276
03/13/2017 209 0 0 0 1 0 0 0 6.1 238.161619 0.008535417 0.120279563 0.062080276
03/13/2017 210 0 0 0 1 0 0 0 7.8 238.161619 0.004056711 0.120279563 0.062080276
03/13/2017 211 0 0 0 1 0 0 0 7.8 238.161619 0.004056711 0.120279563 0.062080276
03/13/2017 212 0 0 0 1 0 0 0 7.8 238.161619 0.004056711 0.120279563 0.062080276
03/14/2017 213 0 0 0 1 0 0 1 6.5 238.161619 0.002868652 0.008901032 0.06205248
03/14/2017 214 0 0 0 1 0 0 1 6.5 238.161619 0.002868652 0.008901032 0.06205248
03/14/2017 215 0 0 0 1 0 0 1 6.5 238.161619 0.002868652 0.008901032 0.06205248
03/14/2017 216 0 1 0 1 0 0 0 6.1 238.161619 0.007473939 0.008901032 0.06205248
03/14/2017 217 0 1 0 1 0 0 0 6.1 238.161619 0.007473939 0.008901032 0.06205248
03/14/2017 218 0 1 0 1 0 0 0 6.1 238.161619 0.007473939 0.008901032 0.06205248
03/14/2017 219 1 0 0 1 0 0 0 7.7 238.161619 0.006994721 0.008901032 0.06205248
03/14/2017 220 1 0 0 1 0 0 0 7.7 238.161619 0.006994721 0.008901032 0.06205248
03/14/2017 221 1 0 0 1 0 0 0 7.7 238.161619 0.006994721 0.008901032 0.06205248
03/14/2017 222 0 0 0 1 0 0 0 6.8 238.161619 0.010898931 0.008901032 0.06205248
03/14/2017 223 0 0 0 1 0 0 0 6.8 238.161619 0.010898931 0.008901032 0.06205248
03/14/2017 224 0 0 0 1 0 0 0 6.8 238.161619 0.010898931 0.008901032 0.06205248
03/15/2017 225 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 226 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 227 0 0 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 228 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 229 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 230 0 0 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 231 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 232 0 1 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 233 0 0 0 1 0 0 1 6.5 238.161619 0.002556912 -0.001296433 0.062024152
03/15/2017 234 0 0 0 1 0 0 0 6.1 238.161619 0.00638285 -0.001296433 0.062024152
03/15/2017 235 0 0 0 1 0 0 0 6.1 238.161619 0.00638285 -0.001296433 0.062024152
03/15/2017 236 0 0 0 1 0 0 0 6.1 238.161619 0.00638285 -0.001296433 0.062024152
03/15/2017 237 0 0 0 0 0 0 0 6.5 238.161619 0.014866991 -0.001296433 0.062024152
03/15/2017 238 0 0 0 0 0 0 0 6.5 238.161619 0.014866991 -0.001296433 0.062024152
03/15/2017 239 0 0 0 0 0 0 0 6.5 238.161619 0.014866991 -0.001296433 0.062024152
03/15/2017 240 0 0 0 1 0 0 0 7.7 238.161619 0.006218225 -0.001296433 0.062024152
03/15/2017 241 0 0 0 1 0 0 0 7.7 238.161619 0.006218225 -0.001296433 0.062024152
03/15/2017 242 0 0 0 1 0 0 0 7.7 238.161619 0.006218225 -0.001296433 0.062024152
04/01/2017 243 0 0 0 1 0 0 1 6.5 192.143176 0.002289305 0.058578409 0.061975502
04/01/2017 244 0 0 0 1 0 0 0 6.1 192.143176 0.005353254 0.058578409 0.061975502
04/02/2017 245 0 0 0 0 1 0 0 6 192.143176 0.003172046 0.058578409 0.061975502
04/03/2017 246 0 0 0 0 0 0 1 6.5 192.143176 0.002848748 0.058578409 0.061975502
04/03/2017 247 0 0 0 0 1 0 0 6.1 192.143176 0.006550344 0.058578409 0.061975502
04/03/2017 248 1 0 0 0 1 0 0 7.3 192.143176 0.007641192 0.058578409 0.061975502
04/03/2017 249 0 0 0 0 0 0 0 7.8 192.143176 0.004299388 0.058578409 0.061975502
04/04/2017 250 0 0 0 1 0 0 1 6.5 192.143176 0.002568017 -0.009146501 0.061948162
04/04/2017 251 0 1 0 0 1 0 0 6.1 192.143176 0.005894783 -0.009146501 0.061948162
04/04/2017 252 0 0 1 1 0 0 0 6.5 192.143176 0.012075672 -0.009146501 0.061948162
04/04/2017 253 0 0 1 1 0 0 0 6.7 192.143176 0.00728987 -0.009146501 0.061948162
04/04/2017 254 0 0 1 1 0 0 0 5.7 192.143176 0.010382549 -0.009146501 0.061948162
04/05/2017 255 0 0 0 0 1 0 1 6.5 192.143176 0.002292826 -0.007230556 0.061920632
04/05/2017 256 0 0 0 0 1 0 0 7.3 192.143176 0.005146235 -0.007230556 0.061920632
04/06/2017 257 1 0 0 1 0 0 1 6.5 192.143176 0.002294755 0.044621463 0.061907235
04/06/2017 258 0 0 0 0 1 0 1 6.5 192.143176 0.002294755 0.044621463 0.061907235
04/06/2017 259 0 0 0 1 0 0 0 6.1 192.143176 0.005304792 0.044621463 0.061907235
04/06/2017 260 0 0 0 0 1 0 0 6.1 192.143176 0.005304792 0.044621463 0.061907235
04/06/2017 261 0 0 0 1 0 0 0 6.1 192.143176 0.005304792 0.044621463 0.061907235
04/06/2017 262 0 0 0 1 0 0 0 6.1 192.143176 0.005304792 0.044621463 0.061907235
04/07/2017 263 0 1 0 1 0 0 1 6.5 192.143176 0.002301431 0.022833827 0.061883181
04/07/2017 264 0 0 0 1 0 0 1 6.5 192.143176 0.002301431 0.022833827 0.061883181
04/08/2017 265 1 0 0 1 0 0 1 6.5 192.143176 0.002278467 0.010542803 0.061856182
04/08/2017 266 1 0 0 1 0 0 1 6.5 192.143176 0.002278467 0.010542803 0.061856182
04/08/2017 267 0 0 0 0 1 0 0 6.1 192.143176 0.00522646 0.010542803 0.061856182
04/09/2017 268 0 1 0 1 0 0 0 7.8 192.143176 0.003720009 0.010542803 0.061856182
04/10/2017 269 0 1 0 1 0 0 1 6.5 192.143176 0.002842283 0.010542803 0.061856182
04/10/2017 270 0 0 0 1 0 0 0 6.1 192.143176 0.006367672 0.010542803 0.061856182
04/10/2017 271 1 0 0 0 1 0 0 6.1 192.143176 0.006367672 0.010542803 0.061856182
04/11/2017 272 0 0 1 1 0 0 0 7.3 192.143176 0.003752301 0.016406649 0.061830366
04/12/2017 273 0 0 0 1 0 0 0 7.8 192.143176 0.003363679 -0.011453291 0.061803585
04/13/2017 274 0 0 0 0 1 0 0 6.1 192.143176 0.004953876 -0.038904987 0.061786866
04/13/2017 275 0 0 0 1 0 0 0 6.1 192.143176 0.004953876 -0.038904987 0.061786866
04/13/2017 276 0 0 0 1 0 0 0 6.1 192.143176 0.004953876 -0.038904987 0.061786866
04/13/2017 277 0 1 0 1 0 0 0 5.7 192.143176 0.005242642 -0.038904987 0.061786866
04/14/2017 278 0 1 0 1 0 0 1 6.5 192.143176 0.00227121 0.010274397 0.061759967
04/14/2017 279 1 0 0 0 1 0 1 6.5 192.143176 0.00227121 0.010274397 0.061759967
04/14/2017 280 0 0 0 1 0 0 0 6.1 192.143176 0.005054546 0.010274397 0.061759967
04/14/2017 281 0 0 0 1 0 0 0 7.8 192.143176 0.00321436 0.010274397 0.061759967
04/15/2017 282 0 1 0 1 0 0 0 4.3 192.143176 0.005754067 0.043387372 0.061472759
05/11/2017 283 0 0 0 0 0 1 0 6.1 193.7951124 0.007689064 0.043387372 0.061472759
05/17/2017 284 0 1 0 1 0 0 1 6.5 193.7951124 0.002436707 0.034476265 0.061448786
05/17/2017 285 0 1 0 1 0 0 0 7.3 193.7951124 0.004911254 0.034476265 0.061448786
05/17/2017 286 1 0 0 0 1 0 0 7.8 193.7951124 0.004096965 0.034476265 0.061448786
05/18/2017 287 1 0 0 0 1 0 1 6.5 193.7951124 0.003189772 0.017341108 0.061423998
05/18/2017 288 0 0 0 1 0 0 1 6.5 193.7951124 0.003189772 0.017341108 0.061423998
05/18/2017 289 0 0 0 1 0 0 1 6.5 193.7951124 0.003189772 0.017341108 0.061423998
05/18/2017 290 0 1 0 1 0 0 1 6.5 193.7951124 0.003189772 0.017341108 0.061423998
05/19/2017 291 0 0 0 1 0 0 1 6.5 193.7951124 0.003154391 0.037870468 0.061407325
05/19/2017 292 0 0 0 1 0 0 0 5.7 193.7951124 0.005666468 0.037870468 0.061407325
05/22/2017 293 1 0 0 1 0 0 1 6.5 193.7951124 0.004100766 0.12857387 0.061498158
05/22/2017 294 0 0 0 1 0 0 0 6.1 193.7951124 0.009390091 0.12857387 0.061498158
05/23/2017 295 0 0 0 1 0 0 0 6.1 193.7951124 0.008675658 -0.004746832 0.061471434
05/24/2017 296 0 0 0 1 0 0 0 4.5 193.7951124 0.005126083 0.099657893 0.061515128
05/25/2017 297 0 0 0 1 0 0 1 6.5 193.7951124 0.003339505 0.035502091 0.061497226
05/25/2017 298 0 0 0 0 1 0 0 6.1 193.7951124 0.007756978 0.035502091 0.061497226
05/25/2017 299 0 0 0 1 0 0 0 6.1 193.7951124 0.007756978 0.035502091 0.061497226
05/25/2017 300 0 0 0 1 0 0 0 6.1 193.7951124 0.007756978 0.035502091 0.061497226
05/26/2017 301 0 1 0 0 1 0 1 6.5 193.7951124 0.003085032 -0.101459299 0.061543369
05/26/2017 302 0 0 0 1 0 0 1 6.5 193.7951124 0.003085032 -0.101459299 0.061543369
05/28/2017 303 0 0 0 1 0 0 1 6.5 193.7951124 0.003484565 -0.000561184 0.061516561
05/28/2017 304 0 0 0 1 0 0 1 6.5 193.7951124 0.003484565 -0.000561184 0.061516561
05/29/2017 305 0 1 0 1 0 0 0 7.8 193.7951124 0.005669722 -0.000561184 0.061516561
05/30/2017 306 0 1 0 1 0 0 0 5.7 193.7951124 0.004592405 -0.002635929 0.061489835
05/31/2017 307 0 1 0 1 0 0 1 6.5 193.7951124 0.003430203 0.016047688 0.061464916
05/31/2017 308 0 1 0 1 0 0 1 6.5 193.7951124 0.003430203 0.016047688 0.061464916
05/31/2017 309 0 0 0 1 0 0 1 6.5 193.7951124 0.003430203 0.016047688 0.061464916
05/31/2017 310 0 0 0 1 0 0 1 6.5 193.7951124 0.003430203 0.016047688 0.061464916
05/31/2017 311 0 1 0 1 0 0 0 5.7 193.7951124 0.004127883 0.016047688 0.061464916
06/01/2017 312 0 0 0 1 0 0 1 6.5 162.775725 0.003417502 0.024917169 0.061442599
06/01/2017 313 0 0 0 1 0 0 0 6.1 162.775725 0.007080266 0.024917169 0.061442599
06/01/2017 314 0 1 0 1 0 0 0 7.3 162.775725 0.00701196 0.024917169 0.061442599
06/02/2017 315 0 0 0 1 0 0 1 6.5 162.775725 0.003507411 0.031259461 0.061422831
06/03/2017 316 0 1 0 1 0 0 1 6.5 162.775725 0.003517714 0.066697292 0.061427601
06/04/2017 317 0 1 0 1 0 0 1 6.5 162.775725 0.003937552 0.066697292 0.061427601
06/05/2017 318 1 0 0 0 0 1 1 6.5 162.775725 0.0043644 0.066697292 0.061427601
06/05/2017 319 0 1 0 1 0 0 0 6.3 162.775725 0.00824234 0.066697292 0.061427601
06/05/2017 320 0 0 0 1 0 0 0 5.7 162.775725 0.008702711 0.066697292 0.061427601
06/06/2017 321 0 0 0 0 1 0 0 6.1 162.775725 0.007922447 0.052613094 0.061420511
06/06/2017 322 1 0 0 0 0 1 0 6.3 162.775725 0.009758651 0.052613094 0.061420511
06/07/2017 323 0 0 0 1 0 0 1 6.5 162.775725 0.003552459 0.02689817 0.061399017
06/07/2017 324 0 0 0 0 1 0 0 6.1 162.775725 0.007161047 0.02689817 0.061399017
06/07/2017 325 0 0 0 1 0 0 0 7.8 162.775725 0.004616254 0.02689817 0.061399017
06/08/2017 326 0 0 0 1 0 0 0 6.1 162.775725 0.007041075 -0.0256721 0.0613771
06/08/2017 327 0 1 0 1 0 0 0 6 162.775725 0.009447309 -0.0256721 0.0613771
06/08/2017 328 0 1 0 1 0 0 0 4.5 162.775725 0.010965946 -0.0256721 0.0613771
06/09/2017 329 0 1 0 1 0 0 1 6.5 162.775725 0.003525695 0.033089851 0.061358282
06/09/2017 330 0 1 0 1 0 0 1 6.5 162.775725 0.003525695 0.033089851 0.061358282
06/09/2017 331 0 0 0 1 0 0 0 6.1 162.775725 0.007052294 0.033089851 0.061358282
06/09/2017 332 0 0 0 1 0 0 0 4.3 162.775725 0.005566463 0.033089851 0.061358282
06/12/2017 333 0 1 0 1 0 0 1 6.5 162.775725 0.004386692 -0.062218475 0.06135903
06/13/2017 334 1 0 0 0 0 1 1 6.5 162.775725 0.003957777 0.029925651 0.061338852
06/14/2017 335 0 0 0 0 0 1 1 6.5 162.775725 0.00353442 -0.072266186 0.061349111
06/14/2017 336 0 0 0 1 0 0 1 6.5 162.775725 0.00353442 -0.072266186 0.061349111
06/14/2017 337 0 0 0 1 0 0 0 6.1 162.775725 0.006936653 -0.072266186 0.061349111
06/14/2017 338 0 0 1 1 0 0 0 7.3 162.775725 0.00475144 -0.072266186 0.061349111
06/14/2017 339 0 1 0 1 0 0 0 7.3 162.775725 0.005299061 -0.072266186 0.061349111
06/15/2017 340 0 1 0 1 0 0 0 6.1 162.775725 0.006977155 -0.093505294 0.061384056
06/15/2017 341 0 0 0 1 0 0 0 8.3 162.775725 0.002227637 -0.093505294 0.061384056
06/15/2017 342 0 0 0 1 0 0 0 7.8 162.775725 0.004187896 -0.093505294 0.061384056
06/15/2017 343 0 0 0 1 0 0 0 7.8 162.775725 0.004187896 -0.093505294 0.061384056
出现错误消息后，我尝试使用“traceback()”命令发现以下内容:
traceback()
4: pmodel.response.pFormula(formula, data, model = model, effect = effect,
theta = theta)
3: pmodel.response(formula, data, model = model, effect = effect,
theta = theta)
2: plm.fit(formula, data, model, effect, random.method, random.dfcor,
inst.method)
1: plm(y ~ x1 + x2 + x3 + x4 * x7 + x5 * x7 + x6 * x7 +
x8 + x9 + x10 + x11, DATA, index = c("year", "id"), model = "within"
我可以在这方面寻求帮助吗？
还是有人可以使用此给定数据尝试此代码，并弄清楚为什么会出现这种错误？
最佳答案
这里发生了两件事，所以这是一个多部分的答案。
1.错误说明
发生此错误的原因是，列“y”中包含的数据具有许多连续重复的值。在343行的样本数据集中，只有82个唯一的“y”值，并且其中许多值连续重复3或4次。这带来了估计具有plm的模型的问题。
要对此进行测试，请尝试用不会重复的值填充“y”；错误将消失。
DATA$y <- rnorm(343)
plm(y ~ x1+x2+x3+x4*x7+x5*x7+x6*x7+x8+x9+x10+x11,
DATA,index=c("Date","ID"),model="within")
输出:
Model Formula: y ~ x1 + x2 + x3 + x4 * x7 + x5 * x7 + x6 * x7 + x8 + x9 + x10 + x11
Coefficients:
x1 x2 x3 x4 x7 x5
0.0266245 -0.0085766 0.6009325 -0.2500684 -1.0461660 0.1972594
x6 x8 x10 x4:x7 x7:x5 x7:x6
0.0668570 0.0432360 -85.6184702 0.8044105 0.9602976 0.5484500
再举一个例子，尝试用x9替换y，x9也恰好有很多连续重复的值。这样做会产生与原始“y”情况相同的错误。
2. PLM应用技巧
既然已经解释了主要错误，那么还有几点要提到。
plm的index参数通常采用相反的顺序:index = c(“ID”，“Date”)而不是index = c(“Date”，“ID”)。因此，这似乎是一个危险信号。我不知道您要测试的是哪种假设，但是有两个提示我仍然会在不知不觉中提及。
如果将“日期”作为ID索引，将“ID”列作为时间索引，则需要按以下方式进行设置:
Date ID
01/01/2017 1
01/01/2017 2
01/02/2017 1
01/02/2017 2
01/03/2017 1
01/03/2017 2
但是，考虑到样本数据中的所有ID仅出现一次，这种情况似乎不太可能。这表明这不是重复测量分析，这意味着索引的顺序可能应该为index = c(“ID”，“Date”)，并且模型可能应该设置为“介于”而不是“在”之内如果每个“ID”列值只有一个观察值。如果第二种情况对于您的情况而言是正确的，请尝试以下方法:
plm(y ~ x1+x2+x3+x4*x7+x5*x7+x6*x7+x8+x9+x10+x11,
DATA,index=c("ID","Date"),model="between")
关于r - plm函数: 'names' attribute [343] must be the same length as the vector [0]中的错误，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/46604729/