> # Load necessary libraries > library(readxl) > library(lavaan) > library(semTools) > library(psych) > library(CCP) > library(CCA) > library(readxl) > datas <- read_excel("C:/Users/ACER/OneDrive - Bina Nusantara/PERKULIAHAN/SEM6/Mulitivariate/aol/DATA_AOL.xlsx") > head(datas) # A tibble: 6 × 30 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 E1 E2 E3 F1 F2 F3 G1 G2 G3 H1 1 6 6 6 6 3 4 3 3 4 5 5 4 5 3 4 3 5 3 3 3 3 3 2 5 4 4 5 4 3 5 5 3 4 4 5 4 4 4 3 4 3 5 6 5 4 3 5 5 5 3 3 3 5 5 5 4 4 3 5 3 3 6 6 6 5 4 4 5 4 4 3 5 3 3 3 6 6 6 4 3 4 5 5 5 4 4 5 5 4 5 5 5 4 5 5 5 4 4 4 5 4 5 3 5 4 4 5 4 3 3 3 3 4 5 6 4 4 4 3 4 4 3 3 3 4 4 4 6 5 5 5 3 3 3 4 5 4 # ℹ 8 more variables: H2 , H3 , I1 , I2 , I3 , J1 , J2 , J3 > # Define CFA model > model <- ' + # Fisik kampus (Physical Campus) + Kebersihan_Kualitas_Fasilitas =~ A1 + A2 + A3 + Keamanan_Lingkungan_Kampus =~ B1 + B2 + B3 + Suasana_Kenyamanan_Lingkungan_Belajar =~ C1 + C2 + C3 + Pencahayaan_Ventilasi_Ruang_Belajar =~ D1 + D2 + D3 + Aksesibilitas_Mobilitas_Area_Kampus =~ E1 + E2 + E3 + + # Kesehatan Mental (Mental Health) + Stress_Akademik =~ F1 + F2 + F3 + Mood_Emosi_Sehari_hari =~ G1 + G2 + G3 + Motivasi_Belajar =~ H1 + H2 + H3 + Kesejahteraan_Mental_Umum =~ I1 + I2 + I3 + Kemampuan_Regulasi_Emosi =~ J1 + J2 + J3 + ' > fit <- cfa(model, data = datas) > summary(fit, fit.measures = TRUE, standardized = TRUE) lavaan 0.6-19 ended normally after 57 iterations Estimator ML Optimization method NLMINB Number of model parameters 105 Number of observations 90 Model Test User Model: Test statistic 454.706 Degrees of freedom 360 P-value (Chi-square) 0.001 Model Test Baseline Model: Test statistic 1235.116 Degrees of freedom 435 P-value 0.000 User Model versus Baseline Model: Comparative Fit Index (CFI) 0.882 Tucker-Lewis Index (TLI) 0.857 Loglikelihood and Information Criteria: Loglikelihood user model (H0) -3304.938 Loglikelihood unrestricted model (H1) -3077.586 Akaike (AIC) 6819.877 Bayesian (BIC) 7082.357 Sample-size adjusted Bayesian (SABIC) 6750.969 Root Mean Square Error of Approximation: RMSEA 0.054 90 Percent confidence interval - lower 0.037 90 Percent confidence interval - upper 0.069 P-value H_0: RMSEA <= 0.050 0.329 P-value H_0: RMSEA >= 0.080 0.001 Standardized Root Mean Square Residual: SRMR 0.077 Parameter Estimates: Standard errors Standard Information Expected Information saturated (h1) model Structured Latent Variables: Estimate Std.Err z-value P(>|z|) Std.lv Std.all Kebersihan_Kualitas_Fasilitas =~ A1 1.000 0.670 0.699 A2 1.108 0.235 4.719 0.000 0.743 0.764 A3 0.882 0.195 4.529 0.000 0.591 0.616 Keamanan_Lingkungan_Kampus =~ B1 1.000 0.547 0.544 B2 1.092 0.235 4.638 0.000 0.597 0.663 B3 1.582 0.380 4.170 0.000 0.865 0.934 Suasana_Kenyamanan_Lingkungan_Belajar =~ C1 1.000 0.781 0.808 C2 1.011 0.162 6.244 0.000 0.789 0.813 C3 0.792 0.139 5.690 0.000 0.619 0.654 Pencahayaan_Ventilasi_Ruang_Belajar =~ D1 1.000 0.795 0.829 D2 0.852 0.136 6.283 0.000 0.678 0.726 D3 0.803 0.128 6.260 0.000 0.638 0.722 Aksesibilitas_Mobilitas_Area_Kampus =~ E1 1.000 0.636 0.717 E2 0.814 0.170 4.777 0.000 0.518 0.587 E3 1.149 0.214 5.376 0.000 0.731 0.835 Stress_Akademik =~ F1 1.000 0.821 0.784 F2 0.827 0.150 5.518 0.000 0.679 0.661 F3 1.016 0.173 5.876 0.000 0.834 0.798 Mood_Emosi_Sehari_hari =~ G1 1.000 0.631 0.644 G2 1.245 0.240 5.196 0.000 0.786 0.830 G3 1.044 0.201 5.207 0.000 0.659 0.721 Motivasi_Belajar =~ H1 1.000 0.561 0.620 H2 1.272 0.240 5.301 0.000 0.714 0.735 H3 1.438 0.277 5.199 0.000 0.807 0.871 Kesejahteraan_Mental_Umum =~ I1 1.000 0.677 0.719 I2 1.043 0.244 4.277 0.000 0.706 0.741 I3 0.749 0.192 3.898 0.000 0.507 0.530 Kemampuan_Regulasi_Emosi =~ J1 1.000 0.718 0.727 J2 1.096 0.197 5.571 0.000 0.786 0.813 J3 0.872 0.166 5.242 0.000 0.626 0.654 Covariances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all Kebersihan_Kualitas_Fasilitas ~~ Kmnn_Lngkngn_K -0.027 0.048 -0.568 0.570 -0.074 -0.074 Ssn_Knymnn_L_B -0.082 0.072 -1.133 0.257 -0.156 -0.156 Pnchyn_Vnt_R_B -0.033 0.072 -0.458 0.647 -0.062 -0.062 Akssblts_M_A_K -0.016 0.058 -0.282 0.778 -0.039 -0.039 Stress_Akademk -0.071 0.076 -0.935 0.350 -0.129 -0.129 Mod_Ems_Shr_hr -0.086 0.061 -1.413 0.158 -0.202 -0.202 Motivasi_Beljr -0.052 0.052 -1.016 0.310 -0.139 -0.139 Ksjhtrn_Mntl_U 0.113 0.069 1.645 0.100 0.250 0.250 Kmmpn_Rgls_Ems -0.053 0.067 -0.790 0.429 -0.110 -0.110 Keamanan_Lingkungan_Kampus ~~ Ssn_Knymnn_L_B -0.026 0.053 -0.498 0.618 -0.062 -0.062 Pnchyn_Vnt_R_B 0.020 0.054 0.375 0.708 0.047 0.047 Akssblts_M_A_K -0.035 0.045 -0.777 0.437 -0.100 -0.100 Stress_Akademk 0.028 0.056 0.505 0.614 0.063 0.063 Mod_Ems_Shr_hr -0.009 0.043 -0.197 0.844 -0.025 -0.025 Motivasi_Beljr -0.068 0.042 -1.607 0.108 -0.222 -0.222 Ksjhtrn_Mntl_U 0.008 0.049 0.174 0.862 0.023 0.023 Kmmpn_Rgls_Ems 0.009 0.049 0.177 0.859 0.022 0.022 Suasana_Kenyamanan_Lingkungan_Belajar ~~ Pnchyn_Vnt_R_B 0.049 0.080 0.609 0.543 0.079 0.079 Akssblts_M_A_K -0.030 0.065 -0.455 0.649 -0.060 -0.060 Stress_Akademk 0.127 0.086 1.478 0.139 0.198 0.198 Mod_Ems_Shr_hr 0.055 0.065 0.839 0.402 0.111 0.111 Motivasi_Beljr -0.002 0.056 -0.044 0.965 -0.006 -0.006 Ksjhtrn_Mntl_U -0.026 0.072 -0.356 0.722 -0.049 -0.049 Kmmpn_Rgls_Ems -0.052 0.074 -0.710 0.478 -0.094 -0.094 Pencahayaan_Ventilasi_Ruang_Belajar ~~ Akssblts_M_A_K -0.156 0.072 -2.166 0.030 -0.307 -0.307 Stress_Akademk -0.066 0.086 -0.769 0.442 -0.101 -0.101 Mod_Ems_Shr_hr 0.141 0.071 1.995 0.046 0.281 0.281 Motivasi_Beljr 0.049 0.058 0.848 0.397 0.110 0.110 Ksjhtrn_Mntl_U -0.078 0.075 -1.035 0.301 -0.144 -0.144 Kmmpn_Rgls_Ems 0.155 0.079 1.953 0.051 0.272 0.272 Aksesibilitas_Mobilitas_Area_Kampus ~~ Stress_Akademk -0.019 0.069 -0.278 0.781 -0.037 -0.037 Mod_Ems_Shr_hr -0.001 0.053 -0.019 0.985 -0.002 -0.002 Motivasi_Beljr -0.005 0.046 -0.109 0.913 -0.014 -0.014 Ksjhtrn_Mntl_U -0.092 0.063 -1.466 0.143 -0.213 -0.213 Kmmpn_Rgls_Ems 0.100 0.064 1.561 0.119 0.218 0.218 Stress_Akademik ~~ Mod_Ems_Shr_hr 0.012 0.068 0.178 0.859 0.023 0.023 Motivasi_Beljr -0.045 0.060 -0.751 0.452 -0.098 -0.098 Ksjhtrn_Mntl_U 0.034 0.077 0.444 0.657 0.061 0.061 Kmmpn_Rgls_Ems -0.038 0.078 -0.481 0.631 -0.064 -0.064 Mood_Emosi_Sehari_hari ~~ Motivasi_Beljr 0.037 0.047 0.803 0.422 0.106 0.106 Ksjhtrn_Mntl_U 0.013 0.059 0.213 0.831 0.030 0.030 Kmmpn_Rgls_Ems 0.065 0.062 1.061 0.289 0.144 0.144 Motivasi_Belajar ~~ Ksjhtrn_Mntl_U -0.064 0.053 -1.205 0.228 -0.170 -0.170 Kmmpn_Rgls_Ems -0.014 0.052 -0.263 0.792 -0.034 -0.034 Kesejahteraan_Mental_Umum ~~ Kmmpn_Rgls_Ems -0.016 0.067 -0.232 0.817 -0.032 -0.032 Variances: Estimate Std.Err z-value P(>|z|) Std.lv Std.all .A1 0.469 0.108 4.336 0.000 0.469 0.511 .A2 0.393 0.116 3.391 0.001 0.393 0.416 .A3 0.572 0.108 5.287 0.000 0.572 0.621 .B1 0.712 0.120 5.950 0.000 0.712 0.704 .B2 0.453 0.094 4.850 0.000 0.453 0.560 .B3 0.110 0.136 0.811 0.417 0.110 0.128 .C1 0.325 0.093 3.485 0.000 0.325 0.347 .C2 0.320 0.094 3.397 0.001 0.320 0.339 .C3 0.512 0.092 5.562 0.000 0.512 0.572 .D1 0.289 0.086 3.366 0.001 0.289 0.313 .D2 0.413 0.083 4.949 0.000 0.413 0.473 .D3 0.375 0.075 4.992 0.000 0.375 0.479 .E1 0.384 0.085 4.509 0.000 0.384 0.487 .E2 0.510 0.089 5.752 0.000 0.510 0.655 .E3 0.233 0.088 2.641 0.008 0.233 0.304 .F1 0.421 0.113 3.717 0.000 0.421 0.385 .F2 0.594 0.110 5.381 0.000 0.594 0.563 .F3 0.398 0.114 3.491 0.000 0.398 0.364 .G1 0.562 0.104 5.398 0.000 0.562 0.585 .G2 0.279 0.101 2.771 0.006 0.279 0.311 .G3 0.401 0.089 4.520 0.000 0.401 0.480 .H1 0.505 0.089 5.697 0.000 0.505 0.616 .H2 0.435 0.098 4.447 0.000 0.435 0.460 .H3 0.207 0.097 2.126 0.033 0.207 0.241 .I1 0.429 0.115 3.730 0.000 0.429 0.484 .I2 0.409 0.120 3.404 0.001 0.409 0.451 .I3 0.659 0.115 5.741 0.000 0.659 0.720 .J1 0.461 0.103 4.492 0.000 0.461 0.472 .J2 0.316 0.101 3.125 0.002 0.316 0.339 .J3 0.525 0.099 5.326 0.000 0.525 0.573 Kbrshn_Klts_Fs 0.449 0.144 3.126 0.002 1.000 1.000 Kmnn_Lngkngn_K 0.299 0.120 2.483 0.013 1.000 1.000 Ssn_Knymnn_L_B 0.610 0.153 3.987 0.000 1.000 1.000 Pnchyn_Vnt_R_B 0.633 0.150 4.217 0.000 1.000 1.000 Akssblts_M_A_K 0.405 0.121 3.360 0.001 1.000 1.000 Stress_Akademk 0.673 0.178 3.791 0.000 1.000 1.000 Mod_Ems_Shr_hr 0.398 0.131 3.030 0.002 1.000 1.000 Motivasi_Beljr 0.315 0.107 2.943 0.003 1.000 1.000 Ksjhtrn_Mntl_U 0.458 0.150 3.052 0.002 1.000 1.000 Kmmpn_Rgls_Ems 0.515 0.149 3.453 0.001 1.000 1.000 > X<-datas[,c("A1","A2","A3","B1","B2","B3","C1","C2","C3","D1","D2","D3","E1","E2","E3")] > Y<-datas[,c("F1","F2","F3","G1","G2","G3","H1","H2","H3","I1","I2","I3","J1","J2","J3")] > n<-nrow(X) > Xc<-scale(X,center = TRUE, scale = FALSE) > Yc<-scale(Y, center = TRUE, scale = FALSE) > cca_result <- cc(Xc,Yc) > print(cca_result) $cor [1] 0.75502941 0.68508046 0.57179337 0.55463383 0.50868693 0.43043021 0.39374220 0.31028895 0.25836469 0.23112940 0.21734382 0.17784318 [13] 0.11800856 0.07506499 0.01876555 $names $names$Xnames [1] "A1" "A2" "A3" "B1" "B2" "B3" "C1" "C2" "C3" "D1" "D2" "D3" "E1" "E2" "E3" $names$Ynames [1] "F1" "F2" "F3" "G1" "G2" "G3" "H1" "H2" "H3" "I1" "I2" "I3" "J1" "J2" "J3" $names$ind.names NULL $xcoef [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] A1 0.149452578 -0.332916950 -0.20855900 0.615310916 0.448032037 0.35610649 0.80847761 0.009527648 -0.25928890 -0.03259993 A2 -0.316813484 -0.502554008 -0.15811890 0.055197505 -0.352788813 0.24339963 -0.63692138 -0.024077760 0.22538007 -0.12284690 A3 0.001775453 0.460662833 0.34243537 -0.284691504 -0.124482234 -0.01574447 0.11625193 -0.106812227 0.04485235 0.35002428 B1 -0.431387405 0.406469063 -0.18697414 -0.259816316 -0.004829712 0.47551298 -0.14944260 -0.245963651 0.37342091 -0.06916279 B2 0.216184720 -0.021370339 0.27324384 0.155313368 -0.678455309 0.55580665 0.18993971 0.586829083 -0.13819260 -0.75985089 B3 0.039165963 -0.577636310 0.19132232 -0.180033611 1.156546519 -0.43811086 0.07535836 -0.174656494 0.16488452 0.44389721 C1 -0.090948086 0.319433938 -0.45136654 -0.349341956 0.445590397 -0.04370750 0.08198533 -0.302575373 -0.78464491 -0.29391980 C2 0.171282066 -0.537386580 0.05391298 -0.198716285 -0.274374629 -0.29795353 0.33009803 0.369995976 0.38945979 0.30031562 C3 0.378296816 -0.386429627 0.17602146 0.014092545 -0.446786822 0.35544629 -0.49227095 -0.173855068 0.35980949 0.36206569 D1 0.568949236 0.495816793 -0.05603672 0.602603918 0.047616480 0.27760962 -0.42094225 -0.343618059 -0.08362834 0.56230130 D2 0.604559125 -0.121668984 0.04539052 -0.880319964 0.154605297 -0.18819125 -0.22557365 -0.355690526 -0.08713043 -0.70422991 D3 -0.602797032 0.125275550 0.32972084 -0.001099585 0.160778890 0.33368498 0.73470663 0.621909749 0.42307777 0.40292038 E1 0.344084895 0.017987899 -0.29145564 0.404395625 -0.361572460 -0.61579924 0.15302660 0.112589849 1.04472800 -0.48719604 E2 -0.352743306 -0.202154096 0.94858609 0.159743203 -0.166766640 0.15816545 0.20148362 -0.658786871 -0.16895081 0.07318995 E3 0.339417506 0.001569524 0.21059596 -0.148609330 0.688111229 0.27943470 -0.91173840 0.610134413 -0.55205872 0.29544664 [,11] [,12] [,13] [,14] [,15] A1 -0.22448898 -0.01508970 -0.113930046 0.45143868 0.20615989 A2 -0.40543968 -0.28206760 0.090226593 -0.74393018 0.02919211 A3 0.09175255 1.00017888 0.107520161 -0.21310473 0.08032420 B1 0.09512312 0.02200025 0.002521805 0.78742705 -0.10297172 B2 0.37211142 0.24934658 0.237930959 -0.38992092 0.18170188 B3 0.12754817 0.05249871 0.155596177 -0.33478425 -0.15822679 C1 -0.11801666 -0.20770416 0.549961387 -0.19542150 0.74447221 C2 -0.44752160 0.26003567 0.405497485 0.30646780 -0.81350655 C3 0.52871331 -0.08042719 -0.410700168 0.05777253 0.49594205 D1 0.22453085 0.03536773 0.582050100 0.03878838 -0.52350409 D2 -0.48125407 0.10690499 -0.314711199 -0.17574873 -0.14993636 D3 -0.28212079 -0.56167006 -0.279752325 -0.24097586 0.54631518 E1 -0.16342497 0.25427115 0.139836923 -0.16644070 0.35548507 E2 -0.10605602 -0.40818730 0.230414677 0.04208714 0.16450892 E3 -0.30883114 0.10131643 0.047584946 0.37190128 -0.22786008 $ycoef [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] F1 0.54451119 0.13901062 -0.59183689 -0.12398465 0.33210720 -0.17164067 0.084461704 0.15416276 -0.21577206 -0.120309692 -0.08817065 F2 -0.16559692 -0.56710116 0.03003066 -0.24732774 -0.54057153 0.20443629 -0.741901600 0.43179525 -0.01253880 0.115523071 -0.36688146 F3 -0.08623393 0.06835066 0.52204613 -0.05461230 -0.10662063 -0.39892551 0.059407365 -0.49638365 0.37134128 0.004685456 0.47010247 G1 0.11600789 -0.19935018 -0.25200232 0.16700266 0.32626716 -0.33528135 0.669594890 0.54430642 -0.10030436 -0.168906703 -0.61169125 G2 -0.16125499 0.68531070 0.09832008 -0.70663078 0.36887781 0.31554798 0.114671264 0.07792076 0.40598043 0.371090879 0.65978338 G3 0.71278771 -0.40652663 -0.07422819 0.57614627 -0.57246865 0.23997890 -0.673265107 0.04984459 -0.09582225 -0.331251952 0.11760621 H1 -0.19799954 0.28089501 0.31011371 -0.34398236 -0.33645762 0.21693838 0.378959262 0.37979338 -0.07500694 -0.318572216 0.31446781 H2 0.10199239 -0.53717143 -0.48281085 -0.39078326 -0.06402832 -0.10464464 0.006168092 -0.53756665 -0.43644422 -0.813280131 -0.02970076 H3 -0.31627549 0.80616460 0.46640446 0.32313879 0.02927219 -0.38927176 0.088257803 0.11049996 0.78053064 0.330831780 -0.61689975 I1 -0.36220545 -0.29250437 -0.17630805 0.23999378 0.36019993 -0.42702315 0.069077536 0.07837406 0.94110862 -0.137124541 0.15488661 I2 0.05768497 0.24895435 -0.40875579 -0.36773411 -0.10640340 0.84594817 -0.105056303 -0.21785029 -0.25487049 0.040516422 -0.40552272 I3 -0.25037239 0.43090386 -0.36859075 0.35163797 -0.45434829 -0.37461583 -0.082902886 -0.02272298 -0.21428933 -0.002750521 0.44413434 J1 0.33899434 0.26269379 -0.55095738 -0.24071618 -0.03299644 -0.69083243 -0.380812434 -0.19025846 -0.31943059 0.235929135 -0.13728410 J2 0.55012675 -0.26150804 0.20506358 0.09344315 -0.15857369 0.57985836 0.206309815 -0.35574602 0.55592435 -0.248950609 -0.08520647 J3 -0.50665688 0.39539717 0.46878158 0.13372376 0.49361417 0.02187478 -0.451442455 0.31603696 -0.30055503 -0.604958717 0.04292025 [,12] [,13] [,14] [,15] F1 0.22274466 -0.882132293 -0.33258878 0.18692962 F2 0.07331754 -0.006707208 0.15643458 -0.17058585 F3 0.43487115 0.754570802 0.08382561 0.36631073 G1 0.40118903 0.295075222 0.21152001 -0.29356882 G2 -0.30920769 -0.051296102 0.41217006 -0.25927775 G3 -0.01619936 0.094975942 0.08979581 0.83063676 H1 -0.47456278 0.238552402 -0.90795023 0.04784966 H2 -0.08304111 0.057953831 0.50503594 -0.13421048 H3 0.38426565 -0.294662962 0.39774997 0.28169179 I1 -0.51824316 0.067970831 -0.08779458 0.15230240 I2 0.37278301 0.342854154 -0.17344982 0.44382569 I3 0.18043455 -0.183900603 -0.04174449 -0.55837836 J1 -0.76638480 0.134498963 -0.16291013 -0.02144952 J2 0.51548717 0.177953318 -0.27494208 -0.63161058 J3 0.20910823 0.038688394 -0.01406051 0.32260019 $scores $scores$xscores [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0.1117819146 0.93229598 -1.78653899 0.62780005 0.361429249 0.92961863 -0.93882660 -1.230618921 2.215674605 0.09047485 [2,] -1.4899508890 0.98030227 -1.06823707 -0.01160456 -0.019651517 0.61606928 2.30417586 0.887620519 -0.512021371 -0.70990438 [3,] 1.1611995584 -0.65799457 -2.54125260 0.54686671 -1.906856305 -1.67298495 0.30177813 -0.768458575 0.788762815 -0.52209253 [4,] 0.8699969873 -0.07857649 0.36480652 0.18868322 -0.876018999 -1.10502891 0.22672639 0.044030191 -0.369894915 1.96908616 [5,] -1.1422230167 0.60688347 0.25251744 0.66130596 -0.099662890 1.19389645 -0.63097613 1.323473576 0.778282246 2.21173348 [6,] 0.3795103668 0.06866574 0.74704960 1.62982473 -0.006488369 -1.57353527 -0.09313315 0.615139966 0.901049195 -1.11654918 [7,] -0.5189564704 1.20785648 0.83394126 -0.40957459 0.362512150 0.24110518 1.57374931 -2.485632801 -1.332200369 -1.05105893 [8,] 0.3158524028 -0.41479340 0.02288433 -0.19888348 0.204917429 -1.84348800 -0.66629721 -2.809618789 -0.407784100 -0.81582597 [9,] -1.0623296912 1.70026391 -2.40596341 0.02718454 0.063200090 0.30352971 0.50963075 -0.998860738 -0.480306001 -0.88775664 [10,] -0.8247584623 0.24417783 -2.19577231 1.11750680 -0.273245602 -1.35832995 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-0.21218817 [36,] 0.38632966 0.109548698 1.094519903 -0.12951305 0.714830603 0.87663699 0.22943617 1.95422158 -1.25835176 -0.77654845 [37,] 1.04078627 -0.310853220 -1.016493046 -1.63966090 -0.567551600 0.05185368 -0.69349925 -0.40673979 -1.66281279 1.45150586 [38,] -0.36227055 -0.743263538 0.354715144 0.12766240 0.137247844 -0.44153323 0.67824471 0.32480918 0.45688955 -0.70600828 [39,] 0.06824982 -0.837053822 0.052938355 0.71510372 -0.334923980 0.15270528 -0.28422409 -1.13012236 2.93928256 0.49540723 [40,] -0.56247242 -0.614383013 -0.131831702 0.48319565 0.856056501 1.82886104 -0.19893050 -1.58176220 -1.30726265 -0.51510645 [41,] -0.50793030 1.118620637 1.667458611 1.25824064 1.236255016 -0.35727552 1.17127667 0.91537676 0.59573726 0.10119609 [42,] -1.47899565 0.176854678 0.412406938 -0.20186979 -0.321699080 0.37654967 0.48438871 -0.41317567 0.92173614 -0.59594192 [43,] -2.46490060 -0.588693233 2.258898026 -0.27732906 0.449802982 -0.61400723 0.92707123 0.08520921 -1.52010198 -1.84503146 [44,] -1.18305190 2.202418136 0.510698635 -1.10965379 1.465991333 0.44903726 -1.45619148 0.69041742 0.16901572 0.15104740 [45,] 0.42195279 0.088685972 0.248047059 0.31864385 -1.274963675 0.75292598 -0.21709033 -0.76602522 -0.01381347 1.86173374 [46,] -0.35747138 0.624364670 -1.725195339 0.31895896 0.611151398 -0.06796517 2.08881670 -0.45205506 0.09958971 0.34046104 [47,] 0.81920575 -0.548879932 0.657013541 1.76354696 -1.782913041 -1.18597618 -0.25906294 1.56765452 -1.24752032 -0.10140811 [48,] 0.22197189 -0.091107636 0.335990926 0.20661581 1.260684203 1.60464835 0.43253382 -1.39673210 0.46345287 -1.04499873 [49,] -0.90589643 1.601628041 1.419087419 -0.89862455 0.478550170 -0.18377698 0.92798271 0.24396974 -0.54492034 -0.88060804 [50,] 0.17295026 -0.909375386 0.108123967 -0.63894648 -1.425588534 -0.08636433 -0.02158743 1.93973210 -0.63344673 0.07661349 [51,] -1.25200154 -0.429580948 -0.607951758 1.92689748 -1.098321835 -0.57619478 -1.73324925 0.66635409 -0.88751510 -1.21511332 [52,] 0.61468100 -0.267723717 1.282234589 1.29912534 -1.143630584 -0.49725392 2.12206140 0.64357478 -0.19128159 -0.77421494 [53,] -0.83945527 -0.194387256 -0.282391514 0.60795137 0.010035545 0.18316480 -0.40740232 -2.35140399 0.21702807 0.24813765 [54,] 0.67413692 -0.113765512 -1.452668569 -1.16622744 -1.004404523 1.45986512 0.33938222 -0.56684159 -0.43221683 -0.75229501 [55,] -2.00408817 -0.234485760 1.370945257 -0.68248356 0.496608122 -2.14156779 -1.02851360 0.79251127 -0.25330725 0.23621186 [56,] -0.12235320 -0.384888187 -0.454185086 0.86139885 -0.538005791 1.60411825 0.57710022 -0.09987591 -0.67901543 0.50872290 [57,] 0.05375980 1.993600417 0.005755442 -0.92845179 -1.043133683 -1.70411504 -0.03739617 -1.12448751 -0.45977835 0.99143376 [58,] 0.04302681 -0.823102073 -1.154084977 0.82582464 -0.622341260 -0.58501810 -0.70243904 0.40289921 0.46008559 0.32965812 [59,] 2.44273187 1.857760665 -0.447085846 0.66877734 1.482502438 -0.82849351 -0.82226297 -0.30889513 0.56672579 0.61080221 [60,] 0.47909764 0.812484179 -1.253807254 0.13107379 -0.551512533 0.79699860 -1.90614953 1.04586740 -1.60891460 -0.20362644 [61,] 0.46271397 0.179140928 0.330789740 1.43898147 -1.472694106 -1.03918675 0.61456304 -1.23472720 -0.37275093 0.07127971 [62,] -0.29758556 0.257634694 0.211057781 0.10759488 -1.319065732 1.18376935 -2.35891452 -0.34402850 1.27962926 -0.80202725 [63,] 0.56268277 0.831734727 -0.211235728 1.15083190 2.013708591 0.49947811 -0.80560385 1.67139456 -1.16229645 -0.24962504 [64,] -0.30415409 -0.721688526 0.246521409 0.12992490 -0.722026433 1.34198369 0.98346917 -0.57060991 1.86570761 -0.47246781 [65,] 0.11427775 -0.121774785 0.461602587 1.12120412 -0.576060554 -0.57539131 0.14584788 0.50889365 -1.36396125 0.94802299 [66,] 0.91777101 -0.442182194 0.653391865 -0.32114952 -0.783697089 0.64805197 0.47867728 1.86444287 0.11075014 0.87972384 [,11] [,12] [,13] [,14] [,15] [1,] -3.136978637 -0.19564461 0.776449564 -0.88173277 -0.078412018 [2,] 0.360539709 -1.26132184 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0.48576706 0.511318847 [33,] 1.341712400 -0.03705189 -0.230811581 0.19594276 0.228166633 [34,] -0.008828498 1.01515296 0.670786627 -1.21042225 0.356860934 [35,] 0.125188223 0.28012964 -0.018255650 -1.75982360 1.981358220 [36,] 0.041039536 -0.89115329 -0.381152483 -0.08075584 0.184519230 [37,] -0.902937347 -0.28109040 0.226719322 -0.10154112 1.460456660 [38,] -0.924403454 1.96809653 -0.226054727 1.09349321 0.198356165 [39,] -1.075731096 1.37781152 -1.896755583 1.54365163 -0.148883160 [40,] -0.144571851 0.14932502 0.395466906 -0.66480368 -0.914831187 [41,] 0.733336513 0.67629414 2.242321992 0.57449501 0.731338632 [42,] -0.313044308 -0.77317824 1.279147392 -0.02521419 0.544869089 [43,] -0.797585948 0.03967932 0.381908132 0.96588087 0.181082083 [44,] -0.343282148 -0.51305701 -2.005244619 -0.30874307 -0.932140922 [45,] 0.360028477 3.12051050 0.225938077 0.35258799 0.207659955 [46,] 0.286221702 1.20339892 0.377205643 -0.30959796 1.182632359 [47,] 0.081674797 1.12786857 -0.122701606 -1.48806334 0.146893537 [48,] 0.354625602 0.35982801 0.281315898 1.26214590 -1.824273713 [49,] 0.255649387 0.84923046 0.955257600 0.68469119 0.119432565 [50,] -0.376607665 0.22743785 -1.332567192 1.31036480 -0.006449440 [51,] 0.557470417 1.46772131 -0.234389920 -0.42703876 1.867940338 [52,] -1.858348044 -0.77608918 0.240082744 -0.30823509 0.518553337 [53,] 2.214329843 -0.36874372 1.615716866 0.16427693 0.292083710 [54,] -0.321435463 -1.08461797 -0.362581256 0.66722831 0.327733921 [55,] 0.715868439 0.34452429 0.020846720 0.40107294 0.198467362 [56,] 0.058157290 -0.56419549 0.205304963 0.36919305 1.162607508 [57,] -0.023740022 -0.73701803 -0.881223139 0.05479527 1.399430050 [58,] -3.066044602 -0.88401366 1.014685715 -0.35110332 -0.614467373 [59,] 1.271833561 -0.14753226 0.435060864 0.50695120 1.247766419 [60,] -1.407569945 0.62560199 0.571619791 3.24714103 -0.093978940 [61,] 0.759461850 -0.12588574 0.098039174 1.31090209 -0.574992689 [62,] 2.333365849 2.21002459 -0.410419409 -0.45643140 0.762386996 [63,] 0.778589233 -0.98583464 1.006158143 1.24203927 0.541685403 [64,] 0.155053923 -0.68651304 -0.990719117 -0.57767022 -0.717530125 [65,] -1.264220093 0.09091636 1.221424761 -0.53960700 -0.320422492 [66,] -1.028582176 -0.85178657 -0.759899441 0.50154973 -0.349575214 [ reached getOption("max.print") -- omitted 24 rows ] $scores$corr.X.xscores [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] A1 0.11554068 -0.307273908 -0.21236396 0.37838521 0.17199856 0.44731217 0.26388797 -0.22387778 -0.08734043 -0.02176708 -0.37640657 A2 -0.33669523 -0.296623289 -0.27741672 0.16421296 -0.02866436 0.41162581 -0.26699734 -0.18586545 0.09360452 0.01779206 -0.43538320 A3 -0.14316946 0.104090129 0.08921174 -0.02151889 -0.04737808 0.16499865 0.03888864 -0.17081825 -0.03266126 0.27377191 -0.29323821 B1 -0.29428247 0.037808046 -0.09543714 -0.22780859 0.25128692 0.48959146 -0.09481924 -0.15268789 0.47268953 -0.27206066 0.12733879 B2 0.10444693 -0.114780309 0.21315545 -0.09330946 0.09234501 0.42403866 0.12503878 0.30185468 0.09321003 -0.47379716 0.45870444 B3 -0.07202842 -0.302175790 0.09883046 -0.11394887 0.61449012 0.10506545 0.03369468 -0.04402433 0.33672203 -0.13935157 0.47479172 C1 0.12902823 -0.062385962 -0.28626177 -0.37717894 -0.07702824 -0.01670066 0.06386291 -0.01362636 -0.16216067 0.15991725 -0.04079556 C2 0.18148117 -0.351537979 -0.12442591 -0.41495618 -0.33774218 -0.01310505 0.22804346 0.15838766 0.02822437 0.32240336 -0.16100311 C3 0.41637043 -0.364786196 -0.09132760 -0.30021482 -0.24721729 0.16855712 -0.06425639 -0.06734149 0.10377252 0.40524606 0.24053471 D1 0.50538540 0.402677557 -0.06049291 0.09588780 0.07321135 0.36616674 0.09570806 -0.19511389 0.19654496 0.20460077 -0.04672902 D2 0.53867003 0.178279328 0.09439898 -0.37499804 0.10954268 0.29610273 0.16285520 -0.26097244 0.16213901 -0.19914343 -0.33148310 D3 0.21303154 0.372922481 0.11631737 -0.25150092 0.09696225 0.30309131 0.29124896 0.25973125 0.31787731 0.27587016 -0.24266829 E1 0.14853598 0.120473182 0.17161575 0.32767273 0.11473059 -0.33651978 -0.20806826 0.07713749 0.46811796 -0.27031269 -0.25881839 E2 -0.11872052 -0.078316431 0.74658416 0.19588999 -0.06555693 -0.14722177 -0.09143952 -0.29623769 -0.03463752 -0.16272638 -0.22655834 E3 0.04176844 0.009376063 0.36417801 0.16574838 0.22730873 -0.06618290 -0.50388579 0.41983893 -0.07818947 -0.05871449 -0.34249597 [,12] [,13] [,14] [,15] A1 0.37483773 -0.20219285 0.0979192 0.11735400 A2 0.23633300 0.03209506 -0.4022201 -0.03650641 A3 0.81019055 -0.07367324 -0.1845756 0.20536412 B1 0.09604468 0.26794679 0.3427495 -0.06040953 B2 0.04199951 0.38197463 -0.1581650 -0.10208188 B3 0.06833489 0.26289974 -0.2112382 -0.11137457 C1 -0.13431626 0.63844683 0.0918395 0.50709955 C2 -0.06472731 0.51806751 0.2393217 -0.06294629 C3 -0.08379160 0.00901177 0.1807006 0.47360360 D1 -0.29509856 0.25013496 -0.2751073 -0.27368849 D2 -0.15903180 -0.25438557 -0.1983521 -0.17040135 D3 -0.41873995 -0.03639625 -0.2492528 0.10187550 E1 0.09681194 0.26250204 0.1934359 0.41959858 E2 -0.10643663 0.27675332 0.2509081 0.17898866 E3 0.14326314 0.10632341 0.3412513 0.27696281 $scores$corr.Y.xscores [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] F1 0.1611761346 -0.05265471 -0.10031884 -0.244536848 0.048532845 -0.127909039 -0.02858506 0.04844048 0.0373986612 -0.015494728 F2 -0.0850450496 -0.18309176 -0.01488392 -0.296079619 -0.131454576 -0.083097212 -0.17773770 0.12421115 0.0554817807 0.010166268 F3 0.0441864967 -0.09094370 0.03635447 -0.230147019 -0.022061204 -0.203202542 -0.02705357 -0.01278071 0.0263552019 0.024851568 G1 0.2032557231 0.04902066 -0.14023793 0.008662395 0.041057815 -0.061832485 0.09572380 0.20229875 -0.0007911759 -0.025208502 G2 0.2373101676 0.21685241 -0.07106591 -0.179269683 0.036796502 0.076197592 -0.02228587 0.13069306 0.0625442940 -0.015022185 G3 0.3770584225 0.11952259 -0.05203299 0.169790405 -0.140435158 0.064681695 -0.01741174 0.11490737 0.0292250624 -0.057595713 H1 0.0021629133 0.13160920 0.09664488 -0.183980318 -0.272390860 -0.027260996 0.13960700 0.08908592 0.0211552866 -0.096532020 H2 -0.0699290687 0.01455221 -0.02773780 -0.183295863 -0.160746108 -0.035152616 0.07581934 -0.08646484 0.0093103726 -0.149912597 H3 0.0006228279 0.29658955 0.10386662 -0.042291834 -0.218101062 -0.055842080 0.05085175 -0.02945625 0.0786107006 -0.060755697 I1 -0.2737641349 -0.11828263 -0.31420276 0.075694906 0.103274739 0.004181186 -0.04986690 0.01476644 0.1530099530 -0.038481424 I2 -0.2386558855 0.14572636 -0.36234299 -0.024806349 0.001637503 0.161415940 -0.02245729 -0.04098577 0.0261374604 0.015065221 I3 -0.2144204510 0.21575150 -0.30679015 0.171550844 -0.184334132 -0.027286793 -0.03863354 0.02914942 0.0097840179 -0.027500290 J1 0.3010625012 0.23185514 -0.02053385 -0.055098701 0.076473487 -0.133294939 -0.16844137 -0.02929149 0.0001810131 -0.002926056 J2 0.3258144865 0.11701814 0.07509023 0.030018027 0.070713653 0.058792537 -0.11547509 -0.05131207 0.0900763652 -0.073529653 J3 -0.0367813519 0.17957808 0.09578193 0.056063515 0.265277269 0.003007350 -0.21831269 0.03760357 -0.0250711325 -0.103435333 [,11] [,12] [,13] [,14] [,15] F1 0.038293021 0.08272024 -0.050801134 -0.023058259 0.0039267540 F2 -0.015065138 0.05402030 -0.003072821 -0.004856203 -0.0020717349 F3 0.067625482 0.09707402 0.031845343 -0.011839923 0.0044855046 G1 -0.011253533 0.03085093 0.057989555 0.017869238 -0.0016651655 G2 0.082783459 -0.01166680 0.015290130 0.035698612 -0.0017560590 G3 0.046659394 -0.02945557 0.017193811 0.027372254 0.0052297477 H1 -0.009370068 -0.03949498 -0.002743656 -0.020560066 0.0024975195 H2 -0.032098102 -0.02510852 -0.022537200 0.029708297 0.0006770698 H3 -0.103467821 -0.01589782 -0.031157289 0.019010928 0.0024658518 I1 0.018012413 -0.01548968 0.013645651 -0.014985419 0.0020891818 I2 -0.038287752 0.03909730 0.038286854 -0.012309608 0.0047446221 I3 0.072491178 0.04953465 0.007636480 -0.000929583 -0.0051077259 J1 -0.066202862 -0.05318128 0.042889182 -0.012545268 -0.0046914319 J2 -0.035848534 0.01233837 0.015594890 -0.017374715 -0.0100580697 J3 -0.006743644 0.01825139 0.020276049 -0.009385340 -0.0032602969 $scores$corr.X.yscores [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] A1 0.08723662 -0.210507351 -0.12142831 0.20986524 0.08749342 0.192536672 0.10390383 -0.069466804 -0.022565682 -0.005031013 A2 -0.25421480 -0.203210820 -0.15862504 0.09107806 -0.01458119 0.177176185 -0.10512812 -0.057671995 0.024184103 0.004112269 A3 -0.10809715 0.071310114 0.05101068 -0.01193511 -0.02410061 0.071020405 0.01531210 -0.053003015 -0.008438515 0.063276736 B1 -0.22219192 0.025901554 -0.05457032 -0.12635035 0.12782637 0.210734953 -0.03733434 -0.047377366 0.122126285 -0.062881216 B2 0.07886051 -0.078633747 0.12188087 -0.05175258 0.04697470 0.182519050 0.04923305 0.093662172 0.024082181 -0.109508450 B3 -0.05438357 -0.207014731 0.05651060 -0.06319990 0.31258309 0.045223342 0.01326702 -0.013660263 0.086997082 -0.032208244 C1 0.09742011 -0.042739403 -0.16368258 -0.20919620 -0.03918326 -0.007188468 0.02514552 -0.004228109 -0.041896590 0.036961577 C2 0.13702362 -0.240831802 -0.07114591 -0.23014873 -0.17180504 -0.005640809 0.08979033 0.049145943 0.007292180 0.074516893 C3 0.31437192 -0.249907896 -0.05222052 -0.16650929 -0.12575620 0.072552078 -0.02530045 -0.020895319 0.026811154 0.093664277 D1 0.38158084 0.275866528 -0.03458945 0.05318262 0.03724166 0.157609227 0.03768430 -0.060541684 0.050780278 0.047289253 D2 0.40671171 0.122135684 0.05397671 -0.20798660 0.05572293 0.127451559 0.06412297 -0.080976867 0.041890995 -0.046027900 D3 0.16084508 0.255481906 0.06650950 -0.13949092 0.04932343 0.130459657 0.11467701 0.080591738 0.082128274 0.063761704 E1 0.11214903 0.082533823 0.09812875 0.18173838 0.05836195 -0.144848279 -0.08192525 0.023934911 0.120945152 -0.062477209 E2 -0.08963748 -0.053653057 0.42689187 0.10864722 -0.03334795 -0.063368698 -0.03600360 -0.091919283 -0.008949113 -0.037610849 E3 0.03153640 0.006423357 0.20823457 0.09192966 0.11562898 -0.028487118 -0.19840110 0.130271383 -0.020201399 -0.013570645 [,11] [,12] [,13] [,14] [,15] A1 -0.081809642 0.066662332 -0.023860486 0.007350304 0.0022022119 A2 -0.094627849 0.042030211 0.003787492 -0.030192651 -0.0006850628 A3 -0.063733513 0.144086861 -0.008694073 -0.013855167 0.0038537698 B1 0.027676299 0.017080891 0.031620014 0.025728493 -0.0011336177 B2 0.099696577 0.007469326 0.045076275 -0.011872658 -0.0019156222 B3 0.103193048 0.012152893 0.031024419 -0.015856594 -0.0020900047 C1 -0.008866663 -0.023887231 0.075342189 0.006893931 0.0095159999 C2 -0.034993031 -0.011511310 0.061136399 0.017964680 -0.0011812214 C3 0.052278732 -0.014901764 0.001063466 0.013564292 0.0088874301 D1 -0.010156263 -0.052481265 0.029518066 -0.020650928 -0.0051359139 D2 -0.072045804 -0.028282720 -0.030019674 -0.014889303 -0.0031976743 D3 -0.052742453 -0.074470043 -0.004295069 -0.018710160 0.0019117494 E1 -0.056252578 0.017217342 0.030977487 0.014520266 0.0078739964 E2 -0.049241055 -0.018929028 0.032659260 0.018834412 0.0033588198 E3 -0.074439383 0.025478372 0.012547072 0.025616024 0.0051973583 $scores$corr.Y.yscores [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] F1 0.2134700078 -0.07685916 -0.17544597 -0.44089782 0.095408082 -0.297165571 -0.07259842 0.15611410 0.144751441 -0.06703919 F2 -0.1126380618 -0.26725585 -0.02603024 -0.53382899 -0.258419409 -0.193056180 -0.45140629 0.40030800 0.214742118 0.04398518 F3 0.0585228814 -0.13274893 0.06357974 -0.41495308 -0.043368922 -0.472091731 -0.06870883 -0.04118969 0.102007755 0.10752232 G1 0.2692023909 0.07155460 -0.24525980 0.01561822 0.080713328 -0.143652755 0.24311287 0.65196890 -0.003062245 -0.10906662 G2 0.3143058583 0.31653568 -0.12428600 -0.32322169 0.072336243 0.177026589 -0.05660017 0.42119792 0.242077562 -0.06499470 G3 0.4993956742 0.17446504 -0.09099964 0.30613063 -0.276073847 0.150272201 -0.04422116 0.37032374 0.113115544 -0.24919250 H1 0.0028646742 0.19210766 0.16902063 -0.33171492 -0.535478392 -0.063334300 0.35456447 0.28710633 0.081881493 -0.41765358 H2 -0.0926176749 0.02124160 -0.04851018 -0.33048085 -0.316002040 -0.081668561 0.19256086 -0.27865910 0.036035778 -0.64860896 H3 0.0008249054 0.43292659 0.18165061 -0.07625181 -0.428753027 -0.129735503 0.12914986 -0.09493167 0.304262555 -0.26286443 I1 -0.3625873778 -0.17265508 -0.54950403 0.13647726 0.203022198 0.009713970 -0.12664859 0.04758931 0.592224709 -0.16649299 I2 -0.3160881967 0.21271423 -0.63369569 -0.04472563 0.003219077 0.375010715 -0.05703551 -0.13208905 0.101164987 0.06518089 I3 -0.2839895340 0.31492870 -0.53654024 0.30930469 -0.362372455 -0.063394234 -0.09811886 0.09394282 0.037869021 -0.11898223 J1 0.3987427459 0.33843490 -0.03591130 -0.09934248 0.150335072 -0.309678402 -0.42779607 -0.09440067 0.000700611 -0.01265982 J2 0.4315255553 0.17080933 0.13132407 0.05412224 0.139012128 0.136590174 -0.29327589 -0.16536866 0.348640387 -0.31813198 J3 -0.0487151246 0.26212699 0.16751143 0.10108203 0.521494170 0.006986846 -0.55445590 0.12118887 -0.097037767 -0.44752132 [,11] [,12] [,13] [,14] [,15] F1 0.17618638 0.46513027 -0.43048686 -0.30717725 0.20925339 F2 -0.06931477 0.30375247 -0.02603897 -0.06469330 -0.11040099 F3 0.31114518 0.54584055 0.26985622 -0.15772895 0.23902873 G1 -0.05177756 0.17347266 0.49140127 0.23805021 -0.08873526 G2 0.38088710 -0.06560162 0.12956798 0.47556937 -0.09357889 G3 0.21468010 -0.16562663 0.14569970 0.36464738 0.27868881 H1 -0.04311173 -0.22207758 -0.02324964 -0.27389685 0.13309069 H2 -0.14768353 -0.14118347 -0.19097937 0.39576765 0.03608048 H3 -0.47605596 -0.08939235 -0.26402568 0.25325957 0.13140315 I1 0.08287520 -0.08709742 0.11563273 -0.19963259 0.11133072 I2 -0.17616214 0.21984142 0.32444134 -0.16398599 0.25283688 I3 0.33353227 0.27852994 0.06471124 -0.01238371 -0.27218637 J1 -0.30459970 -0.29903471 0.36344129 -0.16712541 -0.25000242 J2 -0.16493928 0.06937781 0.13215050 -0.23146229 -0.53598599 J3 -0.03102754 0.10262629 0.17181847 -0.12502952 -0.17373845 > cca_result$cor [1] 0.75502941 0.68508046 0.57179337 0.55463383 0.50868693 0.43043021 0.39374220 0.31028895 0.25836469 0.23112940 0.21734382 0.17784318 [13] 0.11800856 0.07506499 0.01876555 > Sxx<-cov(Xc) > Syy <- cov(Yc) > Sxy<-cov(Xc,Yc) > Syx<-t(Sxy) > inv_Sxx <-solve(Sxx) > inv_Syy<-solve(Syy) > matA <-inv_Sxx%*%Sxy%*%inv_Syy%*%Syx > eigA<-eigen(matA) > a_coef <-eigA$vectors > lambda<-eigA$values > b_coef <- inv_Syy%*%Syx%*%a_coef > canonical_corr<-sqrt(lambda) > cat("Koefiesien kanonik(a) untuk X:\n") Koefiesien kanonik(a) untuk X: > print((a_coef)) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0.107069748 0.239476614 0.15936623 0.424837246 0.246778385 0.26277923 -0.45494279 -0.006488112 -0.15437897 -0.02049534 [2,] -0.226969251 0.361501366 0.12082342 0.038110743 -0.194317919 0.17961023 0.35840546 0.016396409 0.13418986 -0.07723295 [3,] 0.001271957 -0.331367855 -0.26166519 -0.196563317 -0.068565464 -0.01161821 -0.06541675 0.072736704 0.02670480 0.22005771 [4,] -0.309051480 -0.292384738 0.14287258 -0.179388412 -0.002660231 0.35089205 0.08409365 0.167495669 0.22233244 -0.04348214 [5,] 0.154877511 0.015372292 -0.20879386 0.107235061 -0.373696725 0.41014261 -0.10688200 -0.399617299 -0.08227900 -0.47771271 [6,] 0.028058999 0.415510199 -0.14619515 -0.124302985 0.637031859 -0.32329216 -0.04240531 0.118937112 0.09817120 0.27907493 [7,] -0.065156378 -0.229777901 0.34490279 -0.241200783 0.245433517 -0.03225278 -0.04613441 0.206046969 -0.46717260 -0.18478523 [8,] 0.122708673 0.386557425 -0.04119654 -0.137202310 -0.151126978 -0.21986681 -0.18575124 -0.251958870 0.23188189 0.18880623 [9,] 0.271016700 0.277969803 -0.13450331 0.009730102 -0.246092514 0.26229205 0.27700844 0.118391359 0.21422829 0.22762806 [10,] 0.407602544 -0.356655097 0.04281935 0.416063785 0.026227406 0.20485457 0.23687068 0.233996107 -0.04979178 0.35351472 [11,] 0.433113926 0.087519955 -0.03468427 -0.607810944 0.085157404 -0.13887068 0.12693376 0.242217183 -0.05187690 -0.44274420 [12,] -0.431851540 -0.090114260 -0.25194964 -0.000759201 0.088557852 0.24623388 -0.41343073 -0.423506437 0.25189782 0.25331310 [13,] 0.246506841 -0.012939206 0.22271005 0.279212215 -0.199155998 -0.45441253 -0.08611042 -0.076671134 0.62202442 -0.30629660 [14,] -0.252709837 0.145415181 -0.72484324 0.110293611 -0.091855936 0.11671395 -0.11337793 0.448618921 -0.10059224 0.04601399 [15,] 0.243163063 -0.001129003 -0.16092273 -0.102606303 0.379015257 0.20620134 0.51304923 -0.415487701 -0.32869226 0.18574514 [,11] [,12] [,13] [,14] [,15] [1,] -0.19139862 0.01114708 -0.098418147 -0.31297891 -0.13361111 [2,] -0.34567663 0.20836934 0.077941987 0.51576098 -0.01891925 [3,] 0.07822794 -0.73885342 0.092880986 0.14774384 -0.05205768 [4,] 0.08110168 -0.01625205 0.002178454 -0.54591701 0.06673542 [5,] 0.31726105 -0.18419762 0.205535985 0.27032912 -0.11776001 [6,] 0.10874718 -0.03878191 0.134411317 0.23210330 0.10254593 [7,] -0.10062064 0.15343548 0.475082586 0.13548420 -0.48248841 [8,] -0.38155555 -0.19209388 0.350287854 -0.21247173 0.52722920 [9,] 0.45077935 0.05941328 -0.354782177 -0.04005324 -0.32141736 [10,] 0.19143431 -0.02612689 0.502802330 -0.02689168 0.33928017 [11,] -0.41031574 -0.07897299 -0.271862378 0.12184522 0.09717294 [12,] -0.24053532 0.41491762 -0.241663254 0.16706668 -0.35406392 [13,] -0.13933563 -0.18783550 0.120797730 0.11539204 -0.23038795 [14,] -0.09042303 0.30153665 0.199043066 -0.02917869 -0.10661734 [15,] -0.26330848 -0.07484460 0.041106121 -0.25783625 0.14767488 > cat("\nKoefiesien kanonik(b) untuk Y:\n") Koefiesien kanonik(b) untuk Y: > print(b_coef) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] F1 0.29453306 -0.06850413 0.25858807 -0.04747907 0.093052258 -0.054517271 -0.018713740 -0.032574551 -0.033191934 -0.0174821248 F2 -0.08957349 0.27946622 -0.01312113 -0.09471247 -0.151461341 0.064933958 0.164379274 -0.091238226 -0.001928827 0.0167865840 F3 -0.04664503 -0.03368306 -0.22809477 -0.02091341 -0.029873760 -0.126708486 -0.013162580 0.104885737 0.057122946 0.0006808406 G1 0.06275015 0.09823934 0.11010600 0.06395253 0.091415954 -0.106493545 -0.148358653 -0.115011806 -0.015429689 -0.0245437255 G2 -0.08722488 -0.33771963 -0.04295846 -0.27059943 0.103354920 0.100225747 -0.025407115 -0.016464636 0.062451441 0.0539229795 G3 0.38555598 0.20033544 0.03243212 0.22063128 -0.160398514 0.076223161 0.149171844 -0.010532149 -0.014740212 -0.0481340103 H1 -0.10710048 -0.13842445 -0.13549630 -0.13172570 -0.094271191 0.068904927 -0.083964031 -0.080250244 -0.011538220 -0.0462915259 H2 0.05516899 0.26471691 0.21095192 -0.14964778 -0.017939930 -0.033237693 -0.001366632 0.113587694 -0.067137645 -0.1181772182 H3 -0.17107745 -0.39727617 -0.20378356 0.12374379 0.008201699 -0.123642219 -0.019554822 -0.023348612 0.120068011 0.0480729554 I1 -0.19592156 0.14414552 0.07703332 0.09190398 0.100923488 -0.135632981 -0.015305150 -0.016560420 0.144769512 -0.0199254798 I2 0.03120254 -0.12268417 0.17859544 -0.14082127 -0.029812894 0.268693802 0.023276778 0.046031710 -0.039206395 0.0058874156 I3 -0.13542962 -0.21234849 0.16104635 0.13465736 -0.127302673 -0.118987138 0.018368361 0.004801359 -0.032963848 -0.0003996764 J1 0.18336637 -0.12945493 0.24072681 -0.09218061 -0.009245188 -0.219425253 0.084374628 0.040201564 -0.049137592 0.0342827124 J2 0.29757059 0.12887059 -0.08959731 0.03578342 -0.044430352 0.184177178 -0.045710991 0.075169043 0.085517118 -0.0361748546 J3 -0.27405718 -0.19485087 -0.20482219 0.05120860 0.138304480 0.006947963 0.100023754 -0.066778528 -0.046233988 -0.0879061662 [,11] [,12] [,13] [,14] [,15] F1 -0.016338610 -0.029263422 -0.0899257635 0.0173085765 -0.0022734098 F2 -0.067985584 -0.009632205 -0.0006837419 -0.0081411642 0.0020746393 F3 0.087113127 -0.057131866 0.0769219720 -0.0043624503 -0.0044550157 G1 -0.113350473 -0.052706825 0.0300803687 -0.0110079188 0.0035703397 G2 0.122262264 0.040622635 -0.0052291943 -0.0214501434 0.0031532968 G3 0.021793216 0.002128216 0.0096819764 -0.0046731510 -0.0101020787 H1 0.058272985 0.062346415 0.0243183558 0.0472515222 -0.0005819404 H2 -0.005503748 0.010909654 0.0059078923 -0.0262830669 0.0016322475 H3 -0.114315642 -0.050483490 -0.0300383424 -0.0206996937 -0.0034258929 I1 0.028701523 0.068084991 0.0069290387 0.0045690034 -0.0018522788 I2 -0.075146067 -0.048974940 0.0349510179 0.0090266708 -0.0053977409 I3 0.082301057 -0.023704866 -0.0187470771 0.0021724656 0.0067909132 J1 -0.025439661 0.100684980 0.0137110068 0.0084781648 0.0002608659 J2 -0.015789327 -0.067722919 0.0181408028 0.0143085286 0.0076815524 J3 0.007953409 -0.027471916 0.0039439474 0.0007317365 -0.0039234148 > cat("\n korelasi kanonik\n") korelasi kanonik > print(canonical_corr) [1] 0.75502941 0.68508046 0.57179337 0.55463383 0.50868693 0.43043021 0.39374220 0.31028895 0.25836469 0.23112940 0.21734382 0.17784318 [13] 0.11800856 0.07506499 0.01876555 > p<-ncol(X) > q<-ncol(Y) > n<-nrow(datas) > p.asym(canonical_corr,n,p,q,tstat = "Wilks") Wilks' Lambda, using F-approximation (Rao's F): stat approx df1 df2 p.value 1 to 15: 0.03916883 1.06079863 225 672.4217 0.2869582 2 to 15: 0.09110502 0.88109152 196 635.2600 0.8559040 3 to 15: 0.17168093 0.74057540 169 597.1463 0.9904446 4 to 15: 0.25507813 0.67073007 144 558.0928 0.9979685 5 to 15: 0.36840701 0.58016409 121 518.1160 0.9998179 6 to 15: 0.49701608 0.48952688 100 477.2392 0.9999868 7 to 15: 0.61003790 0.42730887 81 435.4962 0.9999958 8 to 15: 0.72196647 0.35675611 64 392.9382 0.9999988 9 to 15: 0.79888224 0.32268421 49 349.6469 0.9999965 10 to 15: 0.85602381 0.30605984 36 305.7611 0.9999695 11 to 15: 0.90433405 0.28705186 25 261.5404 0.9997539 12 to 15: 0.94917133 0.23416043 16 217.5462 0.9991615 13 to 15: 0.98017241 0.16101361 9 175.3797 0.9973506 14 to 15: 0.99401509 0.10971743 4 146.0000 0.9789667 15 to 15: 0.99964785 0.02606796 1 74.0000 0.8721745 > U<-Xc%*%a_coef > V<-Yc%*%b_coef > #cannonical loadings = korelasi asli vas cannonical variates > loading_X <- cor(Xc,U) > loading_Y <- cor(Yc, V) > cat("\n===cannonical loadings: X VS U ====\n") ===cannonical loadings: X VS U ==== > print(round(loading_X,3)) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] A1 0.116 0.307 0.212 0.378 0.172 0.447 -0.264 0.224 -0.087 -0.022 -0.376 -0.375 -0.202 -0.098 -0.117 A2 -0.337 0.297 0.277 0.164 -0.029 0.412 0.267 0.186 0.094 0.018 -0.435 -0.236 0.032 0.402 0.037 A3 -0.143 -0.104 -0.089 -0.022 -0.047 0.165 -0.039 0.171 -0.033 0.274 -0.293 -0.810 -0.074 0.185 -0.205 B1 -0.294 -0.038 0.095 -0.228 0.251 0.490 0.095 0.153 0.473 -0.272 0.127 -0.096 0.268 -0.343 0.060 B2 0.104 0.115 -0.213 -0.093 0.092 0.424 -0.125 -0.302 0.093 -0.474 0.459 -0.042 0.382 0.158 0.102 B3 -0.072 0.302 -0.099 -0.114 0.614 0.105 -0.034 0.044 0.337 -0.139 0.475 -0.068 0.263 0.211 0.111 C1 0.129 0.062 0.286 -0.377 -0.077 -0.017 -0.064 0.014 -0.162 0.160 -0.041 0.134 0.638 -0.092 -0.507 C2 0.181 0.352 0.124 -0.415 -0.338 -0.013 -0.228 -0.158 0.028 0.322 -0.161 0.065 0.518 -0.239 0.063 C3 0.416 0.365 0.091 -0.300 -0.247 0.169 0.064 0.067 0.104 0.405 0.241 0.084 0.009 -0.181 -0.474 D1 0.505 -0.403 0.060 0.096 0.073 0.366 -0.096 0.195 0.197 0.205 -0.047 0.295 0.250 0.275 0.274 D2 0.539 -0.178 -0.094 -0.375 0.110 0.296 -0.163 0.261 0.162 -0.199 -0.331 0.159 -0.254 0.198 0.170 D3 0.213 -0.373 -0.116 -0.252 0.097 0.303 -0.291 -0.260 0.318 0.276 -0.243 0.419 -0.036 0.249 -0.102 E1 0.149 -0.120 -0.172 0.328 0.115 -0.337 0.208 -0.077 0.468 -0.270 -0.259 -0.097 0.263 -0.193 -0.420 E2 -0.119 0.078 -0.747 0.196 -0.066 -0.147 0.091 0.296 -0.035 -0.163 -0.227 0.106 0.277 -0.251 -0.179 E3 0.042 -0.009 -0.364 0.166 0.227 -0.066 0.504 -0.420 -0.078 -0.059 -0.342 -0.143 0.106 -0.341 -0.277 > cat("\n===cannonical loadings: Y VS V ====\n") ===cannonical loadings: Y VS V ==== > print(round(loading_Y,3)) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] F1 0.213 0.077 0.175 -0.441 0.095 -0.297 0.073 -0.156 0.145 -0.067 0.176 -0.465 -0.430 0.307 -0.209 F2 -0.113 0.267 0.026 -0.534 -0.258 -0.193 0.451 -0.400 0.215 0.044 -0.069 -0.304 -0.026 0.065 0.110 F3 0.059 0.133 -0.064 -0.415 -0.043 -0.472 0.069 0.041 0.102 0.108 0.311 -0.546 0.270 0.158 -0.239 G1 0.269 -0.072 0.245 0.016 0.081 -0.144 -0.243 -0.652 -0.003 -0.109 -0.052 -0.173 0.491 -0.238 0.089 G2 0.314 -0.317 0.124 -0.323 0.072 0.177 0.057 -0.421 0.242 -0.065 0.381 0.066 0.130 -0.476 0.094 G3 0.499 -0.174 0.091 0.306 -0.276 0.150 0.044 -0.370 0.113 -0.249 0.215 0.166 0.146 -0.365 -0.279 H1 0.003 -0.192 -0.169 -0.332 -0.535 -0.063 -0.355 -0.287 0.082 -0.418 -0.043 0.222 -0.023 0.274 -0.133 H2 -0.093 -0.021 0.049 -0.330 -0.316 -0.082 -0.193 0.279 0.036 -0.649 -0.148 0.141 -0.191 -0.396 -0.036 H3 0.001 -0.433 -0.182 -0.076 -0.429 -0.130 -0.129 0.095 0.304 -0.263 -0.476 0.089 -0.264 -0.253 -0.131 I1 -0.363 0.173 0.550 0.136 0.203 0.010 0.127 -0.048 0.592 -0.166 0.083 0.087 0.116 0.200 -0.111 I2 -0.316 -0.213 0.634 -0.045 0.003 0.375 0.057 0.132 0.101 0.065 -0.176 -0.220 0.324 0.164 -0.253 I3 -0.284 -0.315 0.537 0.309 -0.362 -0.063 0.098 -0.094 0.038 -0.119 0.334 -0.279 0.065 0.012 0.272 J1 0.399 -0.338 0.036 -0.099 0.150 -0.310 0.428 0.094 0.001 -0.013 -0.305 0.299 0.363 0.167 0.250 J2 0.432 -0.171 -0.131 0.054 0.139 0.137 0.293 0.165 0.349 -0.318 -0.165 -0.069 0.132 0.231 0.536 J3 -0.049 -0.262 -0.168 0.101 0.521 0.007 0.554 -0.121 -0.097 -0.448 -0.031 -0.103 0.172 0.125 0.174