R-squared for Bayesian Regression Models
Bibliographic Data
| ID | 23375725 |
|---|---|
| Authors | Andrew Gelman (0000-0002-6975-2601, Columbia University, corresponding author), Ben Goodrich (Institute for Social and Economic Research and Policy, Columbia University, New York, NY), Jonah Gabry (0000-0001-6437-6144, Institute for Social and Economic Research and Policy, Columbia University, New York, NY), Aki Vehtari (0000-0003-2164-9469, Aalto University) |
| Year | 2019 |
| Volume | 73 |
| Issue | 3 |
| Pages | 307-309 |
| Publication date | 2019-07-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | The American Statistician (JOURNAL) |
| Journal identifiers | ISSN: 0003-1305 • E-ISSN: 1537-2731 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00031305.2018.1549100 |
| OpenAlex | W2904925972 |
| Language | EN |
| Citations received | 72 |
| References cited | 9 |
The usual definition of R2 (variance of the predicted values divided by the variance of the data) has a problem for Bayesian fits, as the numerator can be larger than the denominator. We propose an alternative definition similar to one that has appeared in the survival analysis literature: the variance of the predicted values divided by the variance of predicted values plus the expected variance of the errors.
Analysis of variance · Bayesian probability · Conditional variance · Econometrics · Law of total variance · One-way analysis of variance · Regression analysis · Statistics · Variance (accounting) · Variance inflation factor · Financial Risk and Volatility Modeling · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
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| Unique citing works | 72 |
|---|---|
| Citations per year | 10,29 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 67 |