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Oct 14, 2021
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GLM glossary term #5047

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GLM glossary term
mjhajharia Oct 6, 2021
ea47d09
address comments and fix syntax
OriolAbril Oct 14, 2021
6c69b63
config sphinx to parse dollar math syntax
OriolAbril Oct 14, 2021
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4 changes: 1 addition & 3 deletions docs/source/conf.py
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Expand Up @@ -117,9 +117,7 @@
# myst and panels config
jupyter_execute_notebooks = "off"
myst_heading_anchors = 3
myst_enable_extensions = [
"colon_fence",
]
myst_enable_extensions = ["colon_fence", "deflist", "dollarmath", "amsmath"]
panels_add_bootstrap_css = False

# The reST default role (used for this markup: `text`) to use for all
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11 changes: 11 additions & 0 deletions docs/source/glossary.md
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Expand Up @@ -59,4 +59,15 @@ Posterior

- For more on generating and interpreting the posterior samples, see Statistical Rethinking 2nd Edition By Richard McElreath, chapter 3.

Generalized Linear Model
GLM
In a Generalized Linear Model (GLM), we assume the response variable $y_i$ to follow an
exponential family distribution with mean $\mu_i$, which is assumed to be some (often nonlinear)
function of $x_i^T\beta$. They're considered linear because the covariates affect the distribution
of $Y_i$ only through the linear combination $x_i^T\beta$. Some examples of Generalized Linear
Models are: Linear Regression, ANOVA, Logistic Regression and Poisson Regression

:::{note} Do not confuse these with general linear models
:::

:::::