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multi variable linear regression,
考虑的模型如下：
y= ax1 + bx2+cx3
其中a,b,c为参数， x1,x2,x3为三个变量。
python code 如下：
import statsmodels.api as sm
X=[[544.0, 27.0, 0.0],
[786.0, 17.0, 27.0],
[1246.0, -3.0, 44.0],
[1934.0, 0.0, 41.0],
[2703.0, 0.0, 41.0],
[4472.0, 2.0, 41.0],
[5933.0, -2.0, 43.0],
[7670.0, 0.0, 41.0],
[9651.0, 0.0, 41.0],
[11733.0, 17.0, 41.0],
[14244.0, 78.0, 58.0],
[17007.0, 62.0, 136.0],
[20147.0, 93.0, 198.0],
[23884.0, 149.0, 291.0],
[27447.0, 131.0, 440.0],
[30331.0, 259.0, 571.0],
[33259.0, 457.0, 830.0],
[35223.0, 688.0, 1287.0],
[37427.0, 769.0, 1975.0],
[38123.0, 1771.0, 2744.0]]
Y=[34.0,
38.0,
49.0,
51.0,
60.0,
103.0,
124.0,
171.0,
243.0,
328.0,
475.0,
632.0,
892.0,
1153.0,
1540.0,
2050.0,
2649.0,
3281.0,
3996.0,
4740.0]
# fit the data with OLS model
model = sm.OLS(Y, X).fit()
predictions = model.predict(X) # make the predictions by the model
# Print out the statistics
model.summary()
结果如下：
