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Forecasters who base model selection criteria on the maximization of .pdf
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Forecasters who base model selection criteria on the maximization of R2 should Muitiple Choice be wary that extremely high values of R2 may indicate a definitional relationship rather thon causal as required by the multiple regression models. be aware that the simple R-squared measure is suspect when autocorrelation is present. be aware that R-squared can be made arbitrarliy large by adding additional explanatory variables to the model. instead use the adjusted R-squared measure. All of the options are correct..
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Forecasters who base model selection criteria on the maximization of .pdf
- Forecasters who base model selection criteria on the maximization of R2 should Muitiple Choice be wary that extremely high values of R2 may indicate a definitional relationship rather thon causal as required by the multiple regression models. be aware that the simple R-squared measure is suspect when autocorrelation is present. be aware that R-squared can be made arbitrarliy large by adding additional explanatory variables to the model. instead use the adjusted R-squared measure. All of the options are correct.