Reducing outlier effects with robust regression

When we use the fitlm() function to create a linear model, we can specify the model type. The model specification you give is the model that is fit. If we do not give a model specification, through the parameters of the function, the linear specification will be adopted by default. A linear model contains an intercept and linear terms for each predictor.

The model created is normally affected by the response errors. It is commonly assumed that the response errors follow a normal distribution and that extreme values are rare. However, extreme values called outliers do occur and the linear models are very sensitive to these values. Outliers have a large influence on the fit, because squaring the ...

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