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A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)

2 votes

How to specify nonlinear Bayesian regression model?

You can always apply transformations to your x and y values before doing Bayesian Linear Regression. This looks a lot like power-law to me, so I would try taking the logarithm of both x and y. Here th …
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