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outlier influence and similar regression diagnostics might still have some inefficient computations.
(I improved those as I semi-randomly found computational shortcuts)
article that summarizes sev…
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Hello,
In lecture 30 ( (The Capital Asset Pricing Model and Arbitrage Pricing Theory) Beta was calculated with
`AAPL_results = regression.linear_model.OLS(R-R_F, sm.add_constant(M)).fit()`
but sh…
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**What would you like to submit?** (put an 'x' inside the bracket that applies)
- [ x] question
- [ ] bug report
- [ ] feature request
**Issue description**
The code below calculates …
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Having just added quantile regression to the GLS category, I'm realizing that the category name doesn't really work that well. Quantile regression is not a least-squares method but there's not really …
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From our earlier discussion, I will try to summarize the "is it a reduction" question.
As you are familiar with math formalism, I will try to formulate this question using mathematical language.
…
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Total Points: 7/8
Title & Abstract (0.5/1)
The language you use to describe your approach is incredibly vague and the tone is too informal. Try to be more precise in your language when defining …
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Example 1 (working):
```python
from sklearn.linear_model import LinearRegression, BayesianRidge
import numpy as np
ols = LinearRegression()
ols.fit(np.reshape([1,2],(-1,1)), np.array([2,3])…
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statsmodels is being used by plotly express (for instance for px.scatter with linear regression trend, with parameter trendline="ols")
Example: I've develop a test application in Dash that you can…
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original title: "Exception of RegressionResult.summary() when performing OLS with complex-valued data"
import numpy as np
import statsmodels.formula.api as sm
x = np.linspace(0,…
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## Bug(?)
I want to update the degrees of freedom of my model, to account for fixed effects I have demeaned beforehand.
```python
model.df_model += absorbed_df_count
model.df_resids -= absorb…