This is a demo for linearRegression.
It can soak data from 28.txt and determin for each stock ID, what is its linearRegression function.
Example:
Stock No | data1 | data2
600000 -0.462206333 6.8579
600000 0.031339031 13.877
600000 -0.190607735 -20.7811
600000 -0.034129693 -2.6972
600000 -0.175500589 -11.7043
600000 -0.011428571 -9.393
600000 0.105491329 -8.1181
600000 0.08496732 6.6122
600000 0.174698795 -0.6083
600000 0.113846154 10.1228
600000 -0.08747698 28.7464
600000 0.071644803 2.8652
600000 1.006591337 50.248
600000 0.253871422 16.5076
600000 0.369386228 17.8641
600000 0.434818256 42.8326
600000 0.005714286 -8.1374
600000 -0.329545455 -37.402
600000 -0.378531073 -23.7064
600000 -0.29 -19.2207
600000 -0.151728553 -23.9526
600000 0.654339623 29.3339
600000 0.050182482 25.0161
600000 -0.14639444 -6.6776
600000 0.103816794 16.5939
600000 0.050253573 -6.4496
600000 -0.402985075 -23.3326
600000 -0.047058824 9.7569
600000 -0.043981481 4.1763
600000 0.099273608 2.2712
600000 -0.27753304 -7.148
600000 -0.132113821 -17.3096
600000 -0.005854801 -9.9012
600000 0.051825677 -0.2737
600000 -0.089585666 -3.0141
600000 -0.092250923 -8.692
600000 0.344173442 5.6229
600000 0.021169355 -4.5828
600000 -0.182625864 -12.8508
600000 0.218599034 8.0862
600000 -0.065411298 -5.5969
600000 0.030752916 -6.8109
600000 -0.068930041 -0.4399
600000 0.077348066 14.0758
600000 0.609230769 33.9438
Result is: 回归方程式: Y = 0.00240 + 51.25590*X1
回归显著性检验: 回归平方和： 8998.5462 回归方差： 8998.5462 剩余平方和： 5530.1010 剩余方差： 128.6070 离差平方和： 14528.6472 标准误差： 11.3405 F 检 验： 69.9693 相关系数： 0.7870 剩余分析: 观察值 估计值 剩余值 剩余平方 6.86 -23.69 30.55 933.08 13.88 1.61 12.27 150.51 -20.78 -9.77 -11.01 121.30 -2.70 -1.75 -0.95 0.90 -11.70 -8.99 -2.71 7.35 -9.39 -0.58 -8.81 77.61 -8.12 5.41 -13.53 182.99 6.61 4.36 2.25 5.08 -0.61 8.96 -9.57 91.49 10.12 5.84 4.29 18.36 28.75 -4.48 33.23 1104.08 2.87 3.67 -0.81 0.66 50.25 51.60 -1.35 1.82 16.51 13.01 3.49 12.20 17.86 18.94 -1.07 1.15 42.83 22.29 20.54 422.02 -8.14 0.30 -8.43 71.11 -37.40 -16.89 -20.51 420.79 -23.71 -19.40 -4.31 18.55 -19.22 -14.86 -4.36 19.00 -23.95 -7.77 -16.18 261.73 29.33 33.54 -4.21 17.70 25.02 2.57 22.44 503.62 -6.68 -7.50 0.82 0.68 16.59 5.32 11.27 127.02 -6.45 2.58 -9.03 81.50 -23.33 -20.65 -2.68 7.18 9.76 -2.41 12.17 148.02 4.18 -2.25 6.43 41.32 2.27 5.09 -2.82 7.95 -7.15 -14.22 7.07 50.05 -17.31 -6.77 -10.54 111.10 -9.90 -0.30 -9.60 92.23 -0.27 2.66 -2.93 8.60 -3.01 -4.59 1.58 2.48 -8.69 -4.73 -3.97 15.73 5.62 17.64 -12.02 144.49 -4.58 1.09 -5.67 32.15 -12.85 -9.36 -3.49 12.20 8.09 11.21 -3.12 9.74 -5.60 -3.35 -2.25 5.05 -6.81 1.58 -8.39 70.38 -0.44 -3.53 3.09 9.55 14.08 3.97 10.11 102.19 33.94 31.23 2.71 7.37