Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Bayesian Statistics | 2 |
| Maximum Likelihood Statistics | 2 |
| Monte Carlo Methods | 2 |
| Probability | 2 |
| Programming Languages | 2 |
| Statistical Inference | 2 |
| Computation | 1 |
| Computer Software | 1 |
| Medical Research | 1 |
| Social Science Research | 1 |
| Statistical Distributions | 1 |
| More ▼ | |
Source
| Grantee Submission | 1 |
| Measurement:… | 1 |
Author
| Betancourt, Michael | 1 |
| Brubaker, Marcus A. | 1 |
| Carpenter, Bob | 1 |
| Gelman, Andrew | 1 |
| Goodrich, Ben | 1 |
| Guo, Jiqiang | 1 |
| Hoffman, Matthew D. | 1 |
| Kelter, Riko | 1 |
| Lee, Daniel | 1 |
| Li, Peter | 1 |
| Riddell, Allen | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Reports - Descriptive | 2 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkKelter, Riko – Measurement: Interdisciplinary Research and Perspectives, 2020
Survival analysis is an important analytic method in the social and medical sciences. Also known under the name time-to-event analysis, this method provides parameter estimation and model fitting commonly conducted via maximum-likelihood. Bayesian survival analysis offers multiple advantages over the frequentist approach for measurement…
Descriptors: Bayesian Statistics, Maximum Likelihood Statistics, Programming Languages, Statistical Inference
Download full textCarpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; Lee, Daniel; Goodrich, Ben; Betancourt, Michael; Brubaker, Marcus A.; Guo, Jiqiang; Li, Peter; Riddell, Allen – Grantee Submission, 2017
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…
Descriptors: Programming Languages, Probability, Bayesian Statistics, Monte Carlo Methods
