dgrtwo / empirical-bayes-bookLinks
Introduction to Empirical Bayes: Examples from Baseball Statistics
☆196Updated 4 years ago
Alternatives and similar repositories for empirical-bayes-book
Users that are interested in empirical-bayes-book are comparing it to the libraries listed below
Sorting:
- Exercises for the book Applied Predictive Modeling by Kuhn and Johnson (2013)☆197Updated 8 years ago
- caret models all the way down☆228Updated 3 weeks ago
- vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distr…☆285Updated 8 months ago
- Inside every classical test there is a Bayesian model trying to get out.☆327Updated 9 years ago
- Links to slides for talks at the 2017 rstudio::conf☆144Updated 3 years ago
- R package for exploratory data analysis☆120Updated 7 years ago
- shinystan R package and ShinyStan GUI☆199Updated 8 months ago
- Materials from Stan conferences☆255Updated 4 years ago
- My website☆238Updated 8 months ago
- Notes on generalized linear models☆109Updated 6 years ago
- Tidy machine learning pipelines☆134Updated 8 years ago
- An interactive online reading of McElreath's Statistical Rethinking☆125Updated 7 years ago
- Information Package☆44Updated 9 years ago
- John K. Kruschke's Doing Bayesian Data Analysis: A Tutorial with R and BUGS☆118Updated 8 years ago
- Solutions for the practice problems☆147Updated 5 years ago
- R interface to Bokeh http://hafen.github.io/rbokeh/☆311Updated last year
- 🐢 bayesAB: Fast Bayesian Methods for A/B Testing☆315Updated 4 years ago
- Exploratory and diagnostic machine learning tools for R☆73Updated 4 years ago
- Gradient boosted models☆147Updated last year
- R code to accompany Henrik Brink, Joseph W. Richards, and Mark Fetherolf's book "Real-World Machine Learning"☆61Updated 3 years ago
- This package is DEPRECATED. Please use the packages `grf` or `ranger` instead, which have built-in confidence intervals.☆70Updated 7 years ago
- A simpler ggplot2 syntax, saving half of your typing.☆80Updated 7 years ago
- Links to slides for talks at the 2016 Joint Statistical Meetings in Chicago☆79Updated 3 years ago
- ☆162Updated 8 years ago
- All graphs in “Creating More Effective Graphs”, made with R package ggplot2.☆190Updated 9 years ago
- ☆78Updated 10 years ago
- An R package that makes xgboost models fully interpretable☆256Updated 7 years ago
- useR 2016 workshop materials for "Extracting data from the web APIs and beyond"☆114Updated 8 years ago
- Deprecated. Please use ggridges.☆294Updated 7 years ago
- Local Interpretable Model-Agnostic Explanations (R port of original Python package)☆489Updated 3 years ago