FVU – Fraction of Variance Unexplained
CCA – Canonical Correlation Analysis
PLS – Partial Least Squares
MANOVA – Multivariate Analysis of Variance
LAV – Least Absolute Value
RPCA – Robust Principle Component Analysis
PCC – Pearson Correlation Coefficient
HWB – Helmert Wolf Blocking
CLS – Constrained Least Squares
gCCA – Genaralized Canonical Correlation Analysis
RMS – Root Mean Square
MLE — Maximum Likelihood Estimation
AIC – Alaike Information Criterion
NLMS – Normalized Least Mean Squares filter
SGD – Stochastic Gradient Descent
GRPD – Generalized Randomized Block Design
MAPE – Mean Absolute Percentage Error
PDF – Probability Density Function
LAR – Least Absolute Residual
HC – Heteroscedasticity – Consistent
SAE – Sum of absolute Errors
MAP – maximum a posteriori probability
LARS – Least Angle Regression
EM – Expectation – Maximization
SIC – Schwarz Information Criterion
SMAPE – Symmetric Mean Absolute Percentage Error
SSR – Sum of Squared Residuals
MAPD – Mean Absolute Percentage Deviation
RSS – Residual Sum of Squares
MDA – Mean Directional Accuracy
MPE – Mean Percentage Error
TSS – total Sum of Squares
MISE – Mean Integrated Squared Error
SSE – Sum of Squared Estimate of Errors
MASE – Mean Absolute Scaled Error
EMS – Expected Mean Suares
SSP – Sum of Squares and Products
SDM – Squared of Deviations from the Mean
RMM – Response Modelling Methodology
ESS – Explained Sum of Squares
WMAPE – Weighted Mean Absolute Percentage Error
FPCA – Functional Principal Component Analysis
MSD – Mean Signed Difference
KDE – Kernel Density Estimation
PERMANOVA – Permutational Multivariate Analysis of Variance
MIC – Maximal Information Coefficient
QCR – Quadrant Count Ratio
MSE – Mean Squared Error
PPMCC – Pearson Product Moment Correlation Coefficient
UMP – Uniformly Most Powerful
