使用statsmodel从Python中的GLM中提取系数 [英] Extracting coefficients from GLM in Python using statsmodel

问题描述

我有一个定义如下的模型:

I have a model which is defined as follows:

import statsmodels.formula.api as smf
model = smf.glm(formula="A ~ B + C + D", data=data, family=sm.families.Poisson()).fit()

模型具有如下所示的系数:

The model has coefficients which look like so:

Intercept   0.319813
C[T.foo]   -1.058058
C[T.bar]   -0.749859
D[T.foo]    0.217136
D[T.bar]    0.404791
B           0.262614

我可以通过执行model.params.Intercept和model.params.B来获取Intercept和B的值，但是我无法获取每个C和D的值.

I can grab the values of the Intercept and B by doing model.params.Intercept and model.params.B but I can't get the values of each C and D.

例如，我尝试过model.params.C[T.foo]，但我却得到并出错.

I have tried model.params.C[T.foo] for example, and I get and error.

如何从模型中获取特定值?

How would I get particular values from the model?

推荐答案

model.params是pandas.Series.仅当条目名称是有效的python名称时，才可以作为属性访问.

model.params is is a pandas.Series. Accessing as attribute is only possible if the name of the entry is a valid python name.

在这种情况下，您需要用引号将该名称索引，即model.params["C[T.foo]"]

In this case you need to index with the name in quotes, i.e. model.params["C[T.foo]"]

请参阅 http://pandas.pydata.org/pandas-docs/dev/indexing.html

这篇关于使用statsmodel从Python中的GLM中提取系数的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！