在 R 中使用 lm 时可变长度不同错误

Variable lengths differ error when using lm in R

我正在尝试 运行 线性模型的时间和月因子,但是我收到错误:

Error in model.frame.default(formula = ts.data ~ time2 + factor(month2),  : 
  variable lengths differ (found for 'time2')

我是这样创建变量的:

time2<-seq(along=ts.data)
month2<-rep(1:12,length=length(ts.data))

然而 运行ning length(time2), length(month2) 和 length(ts.data) 给出相同的数字,有谁知道我如何修复错误?

正在尝试 运行 lm :

lm(ts.data~time2+factor(month2))

我正在使用的数据:

structure(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 
64, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 78238, 73928, 70708, 75175, 70744, 65604, 61227, 62635, 
47652, 51507, 81874, 98236, 99401, 94756, 94697, 93732, 100334, 
139355, 88575, 94169, 86084, 98249, 95321, 87822, 80256, 81875, 
86293, 80712, 79533, 82847, 84498, 84185, 78382, 82701, 80491, 
91140, 86847, 96727, 101295, 99450, 87783, 101246, 97913, 100081, 
96346, 93608, 90648, 99105, 90920, 84960, 82591, 88090, 89980, 
87778, 87429, 81898, 77285, 80369, 73193, 65139, 60126, 57219, 
94204, 112472, 157199, 154791.5, 154294.88, 161920.63, 147408.75, 
134418, 132158.5, 104572.5, 96831, 91045.88, 141182.63, 214759.25, 
216647, 184598.38, 210794.38, 182403.75, 193001.63, 176807.38, 
186552.63, 201375.88, 181861.25, 193234.88, 187240.25, 168242, 
172475.13, 188996.25, 179663.88, 192861.63, 187461.25, 188670.5, 
198826.25, 208696.5, 180490.75, 202265.88, 187966.13, 203342.13, 
194850.38, 230582.63, 212517, 223432.5, 196511.63, 229582.25, 
206120.63, 225629.88, 209769.63, 210797.63, 213215.75, 215144.88, 
223266, 230747.63, 228573, 223828.88, 202102.88, 192863.63, 206675.13, 
195647.5, 173897.25, 183788.88, 158511.38, 138559, 114163.25, 
110399.13, 164751.13, 270772, 90430, 81719, 79183, 85428, 79372, 
72361, 66207, 55403, 51693, 60280, 98698, 123059, 121550, 107662, 
107863, 107630, 114685, 169659, 100104, 107598, 97728, 112850, 
107784, 97580, 92709, 99098, 99482, 100543, 98856, 106081, 108248, 
104769, 96966, 100093, 103107, 114944, 108001, 126289, 135213, 
129717, 121688, 134421, 127318, 127412, 121922, 119045, 116989, 
126286, 116707, 106627, 98219, 111225, 117279, 113725, 114633, 
100633, 95478, 98394, 87616, 75329, 68274, 70658, 122995, 145224, 
155833, 131896.5, 138340.63, 145610, 130653.13, 122562.75, 115850.5, 
91749.88, 81787.13, 85457.5, 142931.63, 214970, 216836.63, 175902, 
180757.88, 175233.63, 168982.13, 168727.25, 173501, 182731.38, 
152260.63, 182607, 179326.5, 157693.13, 161004.75, 172990.5, 
166204.38, 175172.63, 186446.13, 202645.38, 202500.25, 204148.38, 
187763.5, 207269.75, 183334.88, 206552.5, 207270.13, 226123.88, 
239037.88, 214656.38, 216552.75, 231406.75, 207365.63, 217873.5, 
200308.88, 201696.5, 208984.75, 227723.38, 212083.25, 206262.38, 
186596.25, 215496.63, 199399, 184933.25, 195925.63, 190318.63, 
170375.38, 171624.13, 154537.13, 133532.25, 119179.13, 113297.88, 
174946.5, 304690, 108567, 99358, 97299, 103628, 96936, 89254, 
83761, 72058, 66685, 74491, 117292, 139878, 139585, 130180, 130079, 
127562, 136152, 197149, 118619, 127875, 118094, 134989, 130688, 
121475, 112367, 114805, 117087, 118526, 118038, 123988, 127511, 
125790, 116702, 123049, 124260, 141232, 133809, 156349, 162637, 
158367, 144491, 164389, 155305, 161401, 151829, 144188, 142702, 
156405, 141937, 129857, 120318, 132823, 138201, 135058, 129275, 
119897, 112924, 120385, 108134, 94062, 86695, 88434, 145426, 
167100, 184196.63, 166628.38, 168193.13, 190280.88, 154984.75, 
153784.38, 148033.75, 121304.25, 107303.25, 108003.13, 168770, 
240983.75, 242817.13, 220229.38, 222805.75, 205068.75, 205204.25, 
192598.25, 206565.38, 227284.88, 199258.25, 227122.88, 209076.13, 
194855.5, 196357.25, 206865.88, 209580.13, 222190.88, 234610.88, 
229339.13, 219321.63, 232571.75, 218584.75, 246116.38, 229563, 
256776.75, 257335.25, 271507, 272014, 265850.5, 253426.63, 291759.63, 
262608.88, 279417.25, 264583.25, 256634.88, 271024.88, 283927.13, 
270597.38, 264222.5, 235009.13, 258379.25, 246485.5, 240163.25, 
238369.88, 240961.5, 219826.75, 212077.5, 194937, 166299, 141284.88, 
130153.38, 206775, 342062.88), .Dim = c(64L, 8L), .Dimnames = list(
    NULL, c("Week_Number", "Campaign_Period", "Control_Traffic", 
    "Control_Revenue", "VOD_Test_Traffic", "VOD_Test_Revenue", 
    "TV_Test_Traffic", "TV_Test_revenue")), .Tsp = c(1, 2.21153846153846, 
52), class = c("mts", "ts", "matrix"))

如果我们根据行数创建分组变量,我们需要更改 'month2' 和 'time2'。

 month2<-rep(1:12,length=nrow(ts.data))
 time2<-seq_len(nrow(ts.data))
 res <- lm(ts.data~time2 + factor(month2))
 coef(res)
 #                            Week_Number Campaign_Period Control_Traffic Control_Revenue VOD_Test_Traffic VOD_Test_Revenue TV_Test_Traffic TV_Test_revenue
 #(Intercept)      0.0000000000000213162821     3.384444444       78799.578     157220.4207       87712.9656      148735.2930     106055.5914      177326.337
 #time2            0.9999999999999994448885    -0.017777778         123.605        727.3023         383.8344         966.6405        465.7336        1229.196
 #factor(month2)2  0.0000000000000152835379     0.017777778       -1177.438       2858.4910       -1320.1678       -8588.9322      -1128.5669       -6726.196
 #factor(month2)3  0.0000000000000008207055     0.035555556        5419.457      10544.3136        6779.6644         346.1573       7382.8661        1173.044
 #factor(month2)4  0.0000000000000016587917     0.053333333        8603.018      27254.5313       12531.1633       23542.1418      12777.1325       28186.515
 #factor(month2)5  0.0000000000000012801265    -0.268888889        3290.677       6985.0394        7531.8356        3638.7607       7201.7339        5969.374
 #factor(month2)6  0.0000000000000020182926    -0.251111111       12858.272       5428.8610       20021.4011        4320.5682      21940.0003        7326.704
 #factor(month2)7  0.0000000000000016906446    -0.233333333        1297.067       6299.8347        3690.1667         327.4537       2400.8667        -451.516
 #factor(month2)8  0.0000000000000016516546    -0.015555556        1838.662       6690.3563        -832.6678       -2303.4348        445.1331        3647.310
 #factor(month2)9  0.0000000000000015682557     0.002222222       -5728.743     -12651.4220       -7622.1022      -22135.3253      -8178.0006      -15978.562
 #factor(month2)10 0.0000000000000003302248     0.020000000       -1715.348      -5722.0704       -2630.9367      -11870.0938      -2470.1342       -9128.055
 #factor(month2)11 0.0000000000000022008184     0.037777778        1179.647      -5052.7747        1691.6289       -8744.7323       2258.9322       -5674.003
 #factor(month2)12 0.0000000000000033608693     0.055555556        5039.042       4606.1469        5908.5944        4559.9012       7788.3986        6991.025