List: Bayesian Statistics | Curated by Dr. Robert Kübler

Apr 27, 2023
11 stories
5 saves
Bayesian Statistics
In
TDS Archive
by
Dr. Robert Kübler
Convenient Bayesian Marketing Mix Modeling With PyMC MarketingA new and shiny library from the PyMC team worth trying out
Apr 13, 2023
118
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Apr 13, 2023
118
5
In
TDS Archive
by
Dr. Robert Kübler
Learning to Rank the Bayesian WayImplement the Bradley–Terry model in PyMC
Aug 9, 2022
245
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Aug 9, 2022
245
6
In
TDS Archive
by
Dr. Robert Kübler
Bayesian Hierarchical Marketing Mix Modeling in PyMCLearn how to build MMMs for different countries the right way
Jul 25, 2022
283
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Jul 25, 2022
283
7
In
TDS Archive
by
Dr. Robert Kübler
Bayesian Marketing Mix Modeling in Python via PyMCEstimate the saturation, carryover, and other parameters all at once, including their uncertainty
Dec 30, 2021
228
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Dec 30, 2021
228
10
In
TDS Archive
by
Dr. Robert Kübler
Rockin‘ Rolling Regression in Python via PyMCLearn how to deal with varying parameters
Dec 3, 2021
212
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Dec 3, 2021
212
6
In
TDS Archive
by
Dr. Robert Kübler
Bayesian Hierarchical Modeling in PyMCCuring your model’s amnesia
Aug 24, 2021
267
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Aug 24, 2021
267
2
In
TDS Archive
by
Dr. Robert Kübler
Bayesian A/B Testing in PyMC3
May 30, 2021
204
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May 30, 2021
204
6
In
TDS Archive
by
Dr. Robert Kübler
Bayesian Linear Regression in Python via PyMC3Learn how to infer model parameters and make predictions for new data, including uncertainty estimations!
Dec 30, 2020
127
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Dec 30, 2020
127
5
In
TDS Archive
by
Dr. Robert Kübler
Conducting Bayesian Inference in Python using PyMC3Revisiting the coin example and using PyMC3 to solve it computationally.
Dec 23, 2020
213
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Dec 23, 2020
213
2
In
TDS Archive
by
Dr. Robert Kübler
Beginner-friendly Bayesian InferenceLet’s do Bayesian inference hands-on with a classical coin example!
Dec 19, 2020
156
3
Dec 19, 2020
156
3
In
TDS Archive
by
Dr. Robert Kübler
A gentle Introduction to Bayesian InferenceLearn about the difference between the frequentist and the Bayesian approach of reasoning
Dec 16, 2020
771
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Dec 16, 2020
771
7