Skip to content

DOC: Update the link to statsmodels package #7849

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/source/learn/core_notebooks/GLM_linear.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -333,7 +333,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Much shorter, but this code does the exact same thing as the previous specification (you can change priors and everything else too if we wanted). `bambi` parses the `formulae` model string, adds random variables for each regressor (`Intercept` and slope `x` in this case), adds a likelihood (by default, a Normal is chosen), and all other variables (`sigma`). Finally, `bambi` then initializes the parameters to a good starting point by estimating a frequentist linear model using [statsmodels](http://statsmodels.sourceforge.net/).\n",
"Much shorter, but this code does the exact same thing as the previous specification (you can change priors and everything else too if we wanted). `bambi` parses the `formulae` model string, adds random variables for each regressor (`Intercept` and slope `x` in this case), adds a likelihood (by default, a Normal is chosen), and all other variables (`sigma`). Finally, `bambi` then initializes the parameters to a good starting point by estimating a frequentist linear model using [statsmodels](https://www.statsmodels.org/).\n",
"\n",
"If you are not familiar with R's syntax, `'y ~ x'` specifies that we have an output variable `y` that we want to estimate as a linear function of `x`."
]
Expand Down