Dev tools · alternatives · 2026
24 alternatives to R Package for Bayesian AB Testing
🐢 bayesAB: Fast Bayesian Methods for A/B Testing. Contribute to FrankPortman/bayesAB development by creating an account on GitHub.
This is an R package that enables Bayesian statistical analysis for A/B testing. It's designed for data scientists and statisticians who need to compare two versions of something using Bayesian methods rather than… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. R Package for Bayesian AB Testing launched in 2017; newer entries below may have overtaken it.
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I'm excited to introduce tea-tasting, a Python package for the statistical analysis of A/B tests It features Student's t-test, Bootstrap, variance reduction using CUPED, power analysis, and other statistical methods. tea-tasting supports a wide range of data backends, including BigQuery, ClickHouse, PostgreSQL, Snowflake, Spark, and more, all thanks to Ibis. I consider it ready for important tasks and use it for the analysis of switchback experiments in my work.
2024 · e10v.me · its alternatives →
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Bayesian git bisect. Contribute to hauntsaninja/git_bayesect development by creating an account on GitHub.
Mar 2026 · github.com · its alternatives →
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Recently I've been working on making LLM evaluations fast by using bayesian optimization to select a sensible subset. Bayesian optimization is used because it’s good for exploration / exploitation of expensive black box (paraphrase, LLM). I would love to hear your thoughts and suggestions on this!
2024 · github.com · its alternatives →
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Hi, I've been working with other colleagues at University of Bristol for the last year to build an R-package that makes bayesian spatio-temporal modeling easy. That is, if you have some problem like predicting sea level rise over time, disease transmissions, etc., this package may be useful for you. It centers on a collection of Shiny apps that guide you through using the various pieces of spatio-temporal modeling packages like R-INLA or inlabru. Hopefully people find this useful. I think the nice part is that we really tried to design the package so you can add it to your modeling tool kit…
2023 · 4dmodeller.github.io · its alternatives →
- 5BA
2019 · brancher.org · its alternatives →
- 6RH
Hi Hacker News! I’m a Bayesian statistician that has been working on applying hierarchical mixture models (originally developed for genomics) to structure text data, and in the process, used these models to build (what started as a personal) tool for conducting literature reviews and deep research. My literature review process starts with a broad search to find a few key papers/groups, and from there expands along their citation networks. I needed to conduct a few rounds of literature reviews during the course of my research and decided to build a tool to facilitate this process. The…
Oct 2025 · sturdystatistics.com · its alternatives →
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A beginners visual approach to Bayesian data analysis
2017 · amazon.com · its alternatives →
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Experimental Global Optimization Algorithm. Contribute to chrisstroemel/Simple development by creating an account on GitHub.
2018 · github.com · its alternatives →
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I decided I wanted to roll my own AB testing app for Django (https://github.com/crobertsbmw/RobertsAB) when I was finished, I came across this: http://stevehanov.ca/blog/index.php?id=132 Which is a very convincing article on why AB testing sucks and with a few extra lines, you can improve your algorithm to select the best test so you never go back and update your code (yeah right.) I then thought, how many tests does this thing have to run to truly figure out which is best? I made 4 tests with probability of success equalling 1/2, 1/4,…
2014 · github.com · its alternatives →
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This little project came about because I kept running into the same problem: cleanly differentiating sensor data before doing analysis. There are a ton of ways to solve this problem, I've always personally been a fan of using kalman filters for the job as its easy to get the double whammy of resampling/upsampling to a fixed consistent rate and also smoothing/outlier rejection. I wrote a little numpy only bayesian filtering/smoothing library recently (https://github.com/hugohadfield/bayesfilter/) so this felt like a fun and very useful first thing to…
2024 · github.com · its alternatives →
- 12AB
2012 · thumbtack.com · its alternatives →
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Applied Econometrics Library for Python. Contribute to mfarragher/appelpy development by creating an account on GitHub.
2019 · github.com · its alternatives →
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This R statistical nmath module re-created in typescript/javascript and handwritten webassembly. - R-js/libRmath.js
2018 · github.com · its alternatives →
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An R package for quick uncertainty intervals. Contribute to jthaman/ciTools development by creating an account on GitHub.
2017 · github.com · its alternatives →
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Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
2019 · github.com · its alternatives →
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Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming.. - lance-format/lance
2023 · github.com · its alternatives →
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A Python toolkit for rule-based/unsupervised anomaly detection in time series - arundo/adtk
2019 · github.com · its alternatives →
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Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow - YuminosukeSato/bsts-causalimpact
Mar 2026 · github.com · its alternatives →
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How to implement the various methods in real life settings
2016 · its alternatives →
- 21
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
2022 · github.com · its alternatives →
- 22
I am excited to announce the release of TabPFN-2.5, our tabular foundation model that now scales to datasets of up to 50,000 samples and 2,000 features - a 5x increase from TabPFN v2, published in the Nature journal earlier this year. TabPFN-2.5 delivers state-of-the-art predictions in one forward pass without hyperparameter tuning across classification and regression tasks. What’s new in 2.5: TabPFN-2.5 maintains the core approach of v2 - a pretrained transformer trained on more than hundred million synthetic datasets to perform in-context learning and output a predictive distribution for…
Nov 2025 · priorlabs.ai · its alternatives →
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Optimize faster with real time data driven insights
2025 · captchify.com · its alternatives →
Also compare
- Tea-tasting, a Python package for the statistical analysis of A/B tests alternatives
- Git bayesect – Bayesian Git bisection for non-deterministic bugs alternatives
- Faster LLM evaluation with Bayesian optimization alternatives
- 4d-Modeller – R library to make Bayesian spatiotemporal modeling easy alternatives
- Brancher – A user-friendly PyTorch module for probabilistic inference alternatives
- Research Hacker News, ArXiv & Google with Hierarchical Bayesian Models alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →