假设有以下随机生成的数据:
- 2列,
- 50行,
- 整数范围在0-100之间。
使用R软件,可以如下进行泊松广义线性模型和诊断绘图:
> col=2
> row=50
> range=0:100
> df <- data.frame(replicate(col,sample(range,row,rep=TRUE)))
> model <- glm(X2 ~ X1, data = df, family = poisson)
> glm.diag.plots(model)
在Python中,这将给我直线预测器与残差图:
import numpy as np
import pandas as pd
import statsmodels.formula.api
from statsmodels.genmod.families import Poisson
import seaborn as sns
import matplotlib.pyplot as plt
df = pd.DataFrame(np.random.randint(100, size=(50,2)))
df.rename(columns={0:'X1', 1:'X2'}, inplace=True)
glm = statsmodels.formula.api.gee
model = glm("X2 ~ X1", groups=None, data=df, family=Poisson())
results = model.fit()
要在Python中绘制诊断图:
model_fitted_y = results.fittedvalues # fitted values (need a constant term for intercept)
model_residuals = results.resid # model residuals
model_abs_resid = np.abs(model_residuals) # absolute residuals
plot_lm_1 = plt.figure(1)
plot_lm_1.set_figheight(8)
plot_lm_1.set_figwidth(12)
plot_lm_1.axes[0] = sns.residplot(model_fitted_y, 'X2', data=df, lowess=True, scatter_kws={'alpha': 0.5}, line_kws={'color': 'red', 'lw': 1, 'alpha': 0.8})
plot_lm_1.axes[0].set_xlabel('Line Predictor')
plot_lm_1.axes[0].set_ylabel('Residuals')
plt.show()
但是当我尝试获取厨师的统计数据时,
# cook's distance, from statsmodels internals
model_cooks = results.get_influence().cooks_distance[0]
它抛出了一个错误,提示:
AttributeError Traceback (most recent call last)
<ipython-input-66-0f2bedfa1741> in <module>()
4 model_residuals = results.resid
5 # normalized residuals
----> 6 model_norm_residuals = results.get_influence().resid_studentized_internal
7 # absolute squared normalized residuals
8 model_norm_residuals_abs_sqrt = np.sqrt(np.abs(model_norm_residuals))
/opt/conda/lib/python3.6/site-packages/statsmodels/base/wrapper.py in __getattribute__(self, attr)
33 pass
34
---> 35 obj = getattr(results, attr)
36 data = results.model.data
37 how = self._wrap_attrs.get(attr)
AttributeError: 'GEEResults' object has no attribute 'get_influence'
是否有一种方法可以在Python中像R语言那样绘制出所有4个诊断图?
如何使用statsmodels
在Python中检索拟合模型结果的cook统计量?