Adjusted R-Squared (R2), corrected Akaike Information Criteria (AICc), Jarque-Bera p-value (JB), Koenker’s studentized Breusch-Pagan p-value (BP), Variance Inflation Factor (VIF), and Global Moran’s I p-value (SA). You may want to sort the models by their AICc values. The ...
or SSE, is a measure of the random error, or the unexplained variation. For each observation, this is the difference between the response value and the predicted value. This is the variation that is not explained by our regression model. This is also referred to as sum of squared err...
多重可决系数 (Multiple R-Squared) 和校正可决系数 (Adjusted R-Squared)的值都可用于测量模型的性能。值的可能范围从 0.0 到 1.0。由于“校正可决系数”的值与数据本身相关因而更能准确地衡量模型的性能,从而反映模型的复杂性(变量数),因此“校正可决系数”值通常要比“多重可决系数”值略小。为模型添加一...
codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 0.9572 on 84 degrees of freedom Multiple R-squared: 0.8051, Adjusted R-squared: 0.7703 F-statistic: 23.13 on 15 and 84 DF, p-value: < 2.2e-16 The understanding raw model outcome is made ...
Adjusted R-squared and RMSE (Root Mean Square Error) are the metrics used to compare the models. The results show that consistent second-order predictors can be derived from log data, implying that students' clicking events in LMS could manifest students' learning strategies understandable in the...
Using the same argument as the one used prior to Equation (21), the sum of squared deviations of the study means about their grand mean can be rewritten as (I − 1)𝑆2𝑋¯𝑖SX¯i2. 𝑆𝑆𝐵 = 𝑛∑𝑖=1𝐼(𝑋¯𝑖−𝑋¯..)2 = 𝑛 (𝐼−1) 𝑆2...
For each variable, we calculated the root-mean-squared error (RMSE) defined as RMSE = ∑ k ( P k − D k ) 2 N , (31) where k refers to the time-step, P to the predicted value from CrunchFlow, D to the measured data, and N to the number of samples. The RMSE is a ...