# Weightened linear model in GLM.jl

**URL:** https://discourse.julialang.org/t/weightened-linear-model-in-glm-jl/119962
**Category:** General Usage
**Tags:** glm
**Created:** [September 27, 2024, 1:22pm UTC](https://discourse.julialang.org/t/weightened-linear-model-in-glm-jl/119962 "2024-09-27T13:22:24Z")
**Posts on this page:** 1
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### Author: ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)
#### Post date: [September 27, 2024, 2:37pm UTC](https://discourse.julialang.org/t/weightened-linear-model-in-glm-jl/119962/2 "2024-09-27T14:37:53Z")

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IIRC weights in GLM are frequency weights, see an old discussion here:

> [@Usage of different types of weights](https://discourse.julialang.org/t/usage-of-different-types-of-weights/4780):
>
> The [weights.jl file](https://github.com/JuliaStats/StatsBase.jl/blob/master/src/weights.jl) describes three types of weights: frequency weights, probability weights, and analytic weights. This is an amazing feature to Julia, as only commercial software like STATA and SAS understand the differences between these 3 weights. R and Python only understand one type of weight, which I think is something like an importance weight. Being able to use these 3 types of weights properly is crucial to the field that I work in (causal machine learning). Most software implementat…

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