RESET suggests augmenting an existing model with the squares or the squares and higher powers of the predictions ( hat y i ) For example, ( left( hat y i 2 ight) ) or ( left( hat y i 2 , hat y i 3 ight) ) or ( left( hat y i 2 , hat y i 3 , hat y i 4 ight) ) What would happen if you augmented the mo...

If you augmented a linear regression model with the predictions fitted values themselves i the following consequences would likely occur No Change in ...

RESET suggests augmenting an existing model with the squares or the squares and higher powers of the

Question:

RESET suggests augmenting an existing model with the squares or the squares and higher powers of the predictions \(\hat{y}_{i}\). For example, \(\left(\hat{y}_{i}^{2}\right)\) or \(\left(\hat{y}_{i}^{2}, \hat{y}_{i}^{3}\right)\) or \(\left(\hat{y}_{i}^{2}, \hat{y}_{i}^{3}, \hat{y}_{i}^{4}\right)\). What would happen if you augmented the model with the predictions \(\hat{y}_{i}\) ?

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