Sentence examples for highest coefficient of determination from inspiring English sources
The highest coefficient of determination between the HYCOM water transport and the measured SSH difference was in the lowest wind speed period, confirming that the HYCOM results are in line with the measured data.
The highest coefficient of determination (0.9925) for Langmuir and BET models indicates best fitness of these models in explaining the sorption as a multilayer process.
The equation using the daily mean outdoor air temperature had the highest coefficient of determination for hot humid climate, compared with other mean temperatures that considered acclimatization of previous days.
The BPVE model yielded the lowest root mean square error and highest coefficient of determination when predicting confined and unconfined compression stress relaxation response of hydrogels (n=15): 0.220±0.316 MPa and 0.93±0.08; and 0.017±0.008 MPa and 0.98±0.01 respectively.
From preliminary simulations, a neural network structure with 20 neurons in the first and 20 neurons in the second hidden layers was selected, which resulted in least mean square error, MSE, and highest coefficient of determination R2, when compared to those of the other model structures considered.
The Langmuir constants obtained from non-linear and linear methods differed even when compared with the results of Langmuir-1 isotherm, which had the highest coefficient of determination for any Langmuir isotherm (Table 2).
Those three models that included combinations of FDXR, ACTN1 and DDB2 had the strongest information theoretic support, lowest mean absolute errors (≤0.13 Gy) and highest coefficients of determination (R2 = 0.96) (Supplementary Table S4).
The pseudo-second-order and Elovich models provided the highest coefficients of determination, but the function Z and the McLintock method confirmed better applicability of the Elovichian model.
The model was found to have the highest coefficients of determination for calibration and cross-validation (0.999, 0.999) and root mean square error of prediction [0.1% (w/w)].
Among single-week lag models, the Lag1 models had the best fit with the highest coefficients of determination (Lag0: 0.91, Lag1: 0.94, Lag2: 0.92).
