自相关残差回归

时间:2020-10-08 22:52:42

标签: statistics regression

我有2个变量X和Y。我想建立回归模型(Y是响应,X是阻遏物)以找到X和Y之间的关系。然后,我将使用相关性来预测其他日期的Y(我在其他日期有x值)。但是,当我检查这些假设时,残差会自动相关(DW测试很重要)。由于我的时间间隔不相等,如何解决自相关问题?

这是我的数据:

Time    X   Y
1/1/2015    216.8160    1.7820
1/5/2015    173.9320    1.6818
1/8/2015    141.4420    1.6480
1/10/2015   142.0990    1.1205
1/15/2015   202.0850    1.8014
1/19/2015   139.1050    1.5689
1/22/2015   77.3665     0.9590
1/23/2015   79.2537     1.2165
1/26/2015   94.2502     1.4657
1/29/2015   94.9671     1.0960
2/1/2015    164.8920    2.2441
2/7/2015    92.8841     0.9361
2/9/2015    95.3771     1.0646
2/12/2015   190.7650    1.7913
2/16/2015   190.8410    2.1200
2/19/2015   223.5520    2.3255
2/22/2015   229.6450    2.6472
2/23/2015   232.7760    2.5560
2/28/2015   219.4150    1.8659
3/1/2015    199.8310    2.2401
3/3/2015    269.8340    3.1491
3/4/2015    269.6200    2.8203
3/7/2015    193.1360    2.1562
3/11/2015   171.4820    2.0335
3/13/2015   188.1430    1.9166
3/14/2015   195.8700    1.7747
3/17/2015   189.3370    2.2283
3/20/2015   237.6840    1.9799
3/24/2015   103.8340    1.4352
3/27/2015   149.0290    1.4497
3/28/2015   128.2730    1.2838
3/30/2015   144.5200    1.3755
4/4/2015    158.3590    1.4340
4/6/2015    172.1230    1.6321
4/11/2015   185.7660    1.9489
4/13/2015   111.8360    1.4299
4/17/2015   173.1580    1.6974
4/24/2015   178.2280    1.9009
4/27/2015   178.5110    1.9542
5/1/2015    220.4470    2.0083
5/3/2015    255.5630    2.8687
5/7/2015    285.2660    2.9606
5/10/2015   279.3760    3.1313
5/14/2015   191.5120    2.3165
5/17/2015   244.7750    2.6072
5/21/2015   211.1450    2.2844
5/24/2015   245.5010    2.5445
5/27/2015   196.5840    2.4106
5/31/2015   210.8370    2.4096
6/3/2015    216.5690    2.1885
6/10/2015   230.0750    2.5330
6/13/2015   223.1900    2.3103
6/17/2015   237.6550    2.6229
6/20/2015   185.1380    2.1995
6/24/2015   240.9690    2.4780
6/27/2015   302.6860    3.4597
7/1/2015    291.2400    2.9420
7/4/2015    281.0320    2.8025
7/9/2015    262.3420    2.8689
7/12/2015   270.4160    2.7998
7/16/2015   270.1910    3.2023
7/19/2015   264.7230    3.5509
7/23/2015   208.0600    2.2068
7/26/2015   180.6280    2.6697
7/30/2015   173.5710    2.4105
8/2/2015    153.4680    2.0625
8/6/2015    80.3503 1.7938
8/9/2015    98.3243 1.9198
8/12/2015   92.3371 1.9848
8/16/2015   100.4340    1.7312
8/19/2015   89.6807 1.7338
8/14/2015   87.7287 1.6029
8/18/2015   89.8975 1.7404
8/20/2015   86.2575 1.4491
8/24/2015   72.0325 1.8491
8/27/2015   75.3284 1.9924
9/1/2015    70.2810 1.3430
9/4/2015    72.0742 1.2466
9/7/2015    88.4218 1.6554
9/10/2015   78.3439 1.0553
9/15/2015   81.8243 1.2442
9/17/2015   74.1898 1.0714
9/21/2015   84.2758 1.4913
9/22/2015   97.1235 1.7594
9/24/2015   65.7313 1.4645
9/27/2015   107.0440    1.8621
9/30/2015   87.4581 1.3534
10/3/2015   75.7782 2.6487
10/13/2015  92.1821 1.1669
10/18/2015  173.7270    1.8870
10/21/2015  127.9350    1.5006
10/24/2015  83.9097 1.3140
10/27/2015  74.4047 1.2053
10/30/2015  81.5380 1.1491
11/2/2015   78.1676 1.3069
11/6/2015   127.1860    2.6453
11/9/2015   123.4270    1.5429
11/14/2015  139.0320    1.5773
11/16/2015  136.1360    1.4705
11/20/2015  147.5160    1.6545
11/24/2015  130.9240    2.9669
11/27/2015  115.3600    1.4209
11/30/2015  160.7920    1.5144
12/4/2015   148.2550    1.4065
12/8/2015   117.0590    1.4141
12/21/2015  140.8640    1.6739
12/22/2015  107.2530    1.4851
12/24/2015  124.3800    1.5657
12/26/2015  127.9850    1.5632
12/29/2015  120.9600    1.5780
1/3/2016    106.0270    1.1630
1/4/2016    107.2760    1.4825
1/7/2016    128.3630    1.2191
1/8/2016    123.9610    1.3272

0 个答案:

没有答案