In this study, to evaluate FFBP scheme and GRNN scheme, the statistics mean squared error (MSE), coefficient of determination (R 2) and coefficient of correlation (r) were used to quantify performance.
The cross-validation statistics investigated include mean squared estimation error (MSE), root mean squared estimation error (RMSE), mean absolute estimation error (MAE), mean of the root variance of the posterior PDFs (MR), the square of Pearson's correlation coefficient, and the square of Spearman's correlation coefficient.
For each model, the following goodness-of fit-statistics are presented: chi-squared, comparative fit index (CFI), standardised root mean square residual (SRMR), root mean squared error of approximation (RMSEA) and Bayesian Information Criteria (BIC).
Global fit was assessed using the two standard statistics of root mean squared error of approximation (RMSEA) [ 40 ] and Tucker Lewis index (TLI) [ 41 ].
Nunes and Balding (2010) proposed using a minimum-entropy algorithm to identify the neighborhood of the true value and then chose the set of summary statistics that minimized the mean squared error across a test data set.
Different from the traditional PCA method, MFKPCA designs three complementary control charts for batch process monitoring based on three statistics including Hotelling's T2, squared prediction error (SPE) and mean squared error (MSE).
The performance of the various data-driven models was evaluated by means of errors statistics criteria such as root mean squared error (RMSE) and coefficient of determination (R 2).
Overall goodness-of-fit statistics were assessed through χ test, the root mean squared error of approximation (RMSEA), baseline comparison index (comparative fit index CFI), and residual size (standardized mean squared residual SMSR).
Other measures like for example mean squared error, can be calculated from the Supporting Information (statistics from simulations).
The models' results were compared using root mean squared error (RMSE) and coefficient of determination (R 2) error statistics.
