方法证据记录
Bayesian Simple linear regression
Bayesian Simple Linear Regression models the relationship between a continuous outcome and a single predictor by combining a Gaussian likelihood with prior distributions over the intercept, slope, and error variance. The result is a full posterior distribution over all parameters, providing probabilistic uncertainty quantification rather than a single point estimate.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Simple Linear Regression
分类方法记录 · regression-model / statistics
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. · ISBN 978-1439840955
- McElreath, R. (2020). Statistical Rethinking: A Bayesian Course with Examples in R and Stan (2nd ed.). CRC Press. · ISBN 978-0367139919
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