Statistics Linear inference and regression Concept
Linear regression
Summary
Linear regression models a response variable as a linear function of explanatory variables plus a random error. The model is linear in the unknown coefficients, not necessarily in the explanatory variables themselves. Its coefficients are most often estimated by ordinary least squares. It is one of the most widely used statistical models, and the base of the general linear model and its extensions.
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| Tag | 41FVC4P5JB |
|---|---|
| URI | m2://41FVC4P5JB |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62J05 |
| Specializes | Statistical model |
| Same as |
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Used by
- Heteroscedasticity
- Ordinary least squares
- Kiefer–Wolfowitz equivalence theorem
- Nonlinear regression
- General linear model
- Quantile regression
- Instrumental variables estimation
- Generalized linear model
- Errors-in-variables model