是否有可能使用 statsmodels 中的 OLS 以手动声明某些系数的方式指定线性回归？
[英]Is there possibility to specify a linear regression using a OLS from statsmodels in way that some coefficients are declare manually?
问题描述
I want to build linear regression by using OLS from statsmodels.
我想通过使用 statsmodels 中的 OLS 来构建线性回归。 I have a question about manually declaration of coefficients for some explanatory variables.我有一个关于手动声明一些解释变量的系数的问题。
Is there possibility to parameterize a model in way that for 4 from 10 variables I will put manually coefficients and for rest the fit method will count the values of them?是否有可能对 model 进行参数化，对于 10 个变量中的 4 个，我将手动放置系数，对于 rest，拟合方法将计算它们的值？
Or maybe you know a different way haw to do it?或者，也许您知道另一种方法来做到这一点？
Many thanks for all answers!非常感谢所有的答案！
MP国会议员
1 个解决方案
解决方案1
1 已采纳 2021-03-01 16:38:37
Yes, in two steps.是的，分两步。 First you take those manual coefficients, multiply them with the corresponding ('manual') variables to get vectors, and subtract them from the target.首先，您获取这些手动系数，将它们与相应的（“手动”）变量相乘以获得向量，然后从目标中减去它们。 Then, you can take a normal OLS and get the coefficients of the remaining variables.然后，您可以采用正态 OLS 并获取剩余变量的系数。
Say you have two variables, x1 and x2 , and want to set the weight for w1 .假设您有两个变量x1和x2 ，并且想要设置w1的权重。 You can simply infer你可以简单地推断
w2 =(x2**T * x2) ** (-1) * x2 ** T * (y - w1 * x1)
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