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| | Bayesian Statistics: A Beginner's Guide
| | dm13450.github.io
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| | Weighted regression is common in frequentist approaches to regression. Typically, the weights are known and can be interpreted as the amount each data point is allowed to influence the link between the variables in question. This can be written as \(\mathbf{y} = \sum _i w_i \beta _i x_i\) where \(w_i\) is the 'weighting'.
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