PERFORMANCE EVALUATION OF CANONICAL CORRELATION ANALYSIS AND REDUNDANCY ANALYSISUSING GAUSSIAN, GAMMA, EXPONENTIAL AND BETA DISTRIBUTED DATA
Abstract
This study was embarked to examine the performance evaluation of canonical correlation and redundancy analysis with some continuous distributed data (Gaussian, Gamma, Exponential and Beta). The objectives of the study were to: obtain the relative efficiency of CCA and RDA techniques for four continuous distributed simulated data; and determine the model performance adequacy of CCA and RDA techniques. Three variates of the response variable (Y1, Y2, Y3) and three variates of independent variables (X1, X2, X3) were used for the simulation. The means used for response and independent variables for the Gaussian distribution were 80, 85 and 90, whereas their standard deviations were 10, 12 and 15. The alpha values used for response and independent variables for the Gamma distribution were 80, 85 and 90 whereas their theta values were 40, 43 and 45. The rates parameters used for response and independent variables for the Exponential distribution were 0.5. 0.7 and 0.9; whereas the shape parameters used for the Beta distribution were taking from 2 to 5 values. The adequacy of the CCA and RDA was evaluated with Wilcoxon rank sum test; and the study concluded thatRDA was more efficient than that of CCA for the Beta distributed data, while for Gaussian, Gamma and Exponential distributed data, the relative efficiency of the CCA and RDA was the same. The study also concluded that the X-variates of the CCA and RDA did not differ.
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