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  2. Mean absolute error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_error

    The MAE is conceptually simpler and also easier to interpret than RMSE: it is simply the average absolute vertical or horizontal distance between each point in a scatter plot and the Y=X line. In other words, MAE is the average absolute difference between X and Y.

  3. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In control theory, the RMSE is used as a quality measure to evaluate the performance of a state observer. [ 10 ] In fluid dynamics , normalized root mean square deviation (NRMSD), coefficient of variation (CV), and percent RMS are used to quantify the uniformity of flow behavior such as velocity profile, temperature distribution, or gas species ...

  4. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

    Asymptotic normality of the MASE: The Diebold-Mariano test for one-step forecasts is used to test the statistical significance of the difference between two sets of forecasts. [ 5 ] [ 6 ] [ 7 ] To perform hypothesis testing with the Diebold-Mariano test statistic, it is desirable for D M ∼ N ( 0 , 1 ) {\displaystyle DM\sim N(0,1)} , where D M ...

  5. Mean squared prediction error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_prediction_error

    And if two models are to be compared, the one with the lower MSPE over the n – q out-of-sample data points is viewed more favorably, regardless of the models’ relative in-sample performances. The out-of-sample MSPE in this context is exact for the out-of-sample data points that it was computed over, but is merely an estimate of the model ...

  6. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    To minimize MSE, the model could be more accurate, which would mean the model is closer to actual data. One example of a linear regression using this method is the least squares method—which evaluates appropriateness of linear regression model to model bivariate dataset, [6] but whose limitation is related to known distribution of the data.

  7. Fannie Mae vs. Freddie Mac: What’s the difference? - AOL

    www.aol.com/finance/fannie-mae-vs-freddie-mac...

    Fannie Mae and Freddie Mac only buy loans that conform to the FHFA’s standards. That means they must be under a certain loan limit and borrowers must meet specific financial requirements.

  8. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    The use of the MAPE as a loss function for regression analysis is feasible both on a practical point of view and on a theoretical one, since the existence of an optimal model and the consistency of the empirical risk minimization can be proved. [1]

  9. Ginnie Mae vs. Fannie Mae: Key Differences - AOL

    www.aol.com/finance/ginnie-mae-vs-fannie-mae...

    A final significant difference between Ginnie Mae and Fannie Mae is that Ginnie Mae has the explicit support of the federal government. This means that if Ginnie Mae has financial difficulties ...