The predictive accuracy of the model will be assessed using calibration, which evaluates the correspondence between the model's predicted percentage of randomized patients and the observed percentage of randomized patients.
Results showed that the model's curve of predicted percentage of dissatisfied (PPD) substantially overestimated the actual percentage of dissatisfied within the partial group of respondents who voted TS > 0 in winter as well as within the partial group of respondents who voted TS < 0 in summer.
Outputs of these models take the form of the predicted percentage change in demand associated with a 1% increase in the price of each food.
The deviation between observed and predicted percentage according to linear, interaction and quadratic models were 0.63 28.76, 1.53 28.76 and 0.15 7.74 % suggesting that the quadratic model has the lowest error.
Applying the model to 7 different annual flow regimes showed substantial year-to-year differences in predicted percentage and mass nitrate-N removal performance.
The validated CFD model predicted that the percentage of the parameter f increased and Vfully mixed/Vtotal decreased as n was increased from 0.11 to 0.99.
The computational model predicted a peak percentage conversion of methane to hydrogen of approximately 59% while experimental results show a peak of approximately 73%.
In addition to the qualitative agreement, the model predicted quantitatively the percentage of membrane vesiculation by endophilin mutants with a varying overall area, A ins, occupied in the membrane plane by the amphipathic helices belonging to one BAR domain.
Regression equations showed a significant percentage of predictive model predicted life differences (PLD) can be captured by utilizing a relationship between PLD and the difference between as-built and job mix formula (JMF) effective dynamic modulus (|E*|) values.
The model predicts the percentage of differentially expressed elements by calculating the proportion of variation arising from the sample treatment, as opposed to the variation introduced by experimental effects [ 3].
The models predicted large percentage decreases for NOx between 2001 and 2010 (61%) and with less pronounced decreases from 2001 to 2020 and 2030 (overall decreases of 78% and 81%, respectively).
