Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Regressão Linear Simples Bayesiana× | Regressão por Mínimos Quadrados Ordinários (MQO)× | |
|---|---|---|
| Área≠ | Estatística | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | Early 19th century; textbook synthesis 2013 | 2019 |
| Autor original≠ | Laplace, P.-S. (early 19th c.); modern treatment: Gelman et al. | Wooldridge (textbook treatment); classical least squares |
| Tipo≠ | Bayesian linear regression | Linear regression |
| Fonte seminal≠ | 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 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Outros nomes | Bayesian SLR, Bayesian univariate regression, probabilistic simple linear regression, Bayesian linear model | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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