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== Log-log linear regression models ==
Log–log plots are often use for visualizing log-log linear regression models with (roughly) [[log-normal]], or [[Log-logistic distribution|Log-logistic]] errors. In such models, after log-transforming the dependent and independent variables, a [[Simple linear regression]] model can be fitted, with the errors becoming [[Homoscedasticity|homoscedastic]]. This model is useful when dealing with data that exhibits exponential growth or decay, while the errors continue to grow as the independent value grows (i.e., [[heteroscedasticity|heteroscedastic]] error).
As above, in a log-log linear model the relationship between the variables is expressed as a power law. Every unit change in the independent variable will result in a constant percentage change in the dependent variable. The model is expressed as:
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