python条件边际效应趋势图代码
时间: 2023-06-10 22:02:35 浏览: 50
我理解了你的问题,以下是一个绘制Python条件边际效应趋势图的示例代码:
```
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
# 创建模拟数据
np.random.seed(123)
N = 1000
X = np.random.randn(N, 2)
beta = np.array([1, -2, 3])
y = np.dot(np.hstack([np.ones((N, 1)), X, X[:, 1:2] ** 2]), beta) + np.random.randn(N)
# 拟合一个线性模型
model = sm.OLS(y, sm.add_constant(X))
results = model.fit()
# 计算条件边际效应
X_grid = np.linspace(np.percentile(X[:, 1], 1), np.percentile(X[:, 1], 99), 20)
X1, X2 = np.meshgrid(np.mean(X[:, :1]), X_grid)
X_test = np.hstack([X1.reshape(-1, 1), X2.reshape(-1, 1)])
y_test = results.predict(sm.add_constant(X_test), transform=False)
dy_dx2 = (y_test[2:] - y_test[:-2]) / (X_grid[2:] - X_grid[:-2])
# 绘制条件边际效应趋势图
fig, ax = plt.subplots()
ax.plot(X_grid[1:-1], dy_dx2)
ax.set_xlabel('X2')
ax.set_ylabel('Conditional Marginal Effect')
plt.show()
```
这段代码将会拟合一个线性模型,然后计算X2的条件边际效应并绘制趋势图。我希望这个代码能够帮到你!