library(readxl)
library(REdaS)
## Loading required package: grid
library(psych)
library(DT)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(FactoMineR)
library(factoextra)
## Loading required package: ggplot2
##
## Attaching package: 'ggplot2'
## The following objects are masked from 'package:psych':
##
## %+%, alpha
## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
data <- read_excel("C:/Users/LENOVO/Downloads/dataset-uci.xlsx")
data
## # A tibble: 319 × 39
## `Gallstone Status` Age Gender Comorbidity `Coronary Artery Disease (CAD)`
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0 50 0 0 0
## 2 0 47 0 1 0
## 3 0 61 0 0 0
## 4 0 41 0 0 0
## 5 0 42 0 0 0
## 6 0 96 0 0 0
## 7 0 37 0 0 0
## 8 0 41 0 0 0
## 9 0 38 0 0 0
## 10 0 38 0 0 0
## # ℹ 309 more rows
## # ℹ 34 more variables: Hypothyroidism <dbl>, Hyperlipidemia <dbl>,
## # `Diabetes Mellitus (DM)` <dbl>, Height <dbl>, Weight <dbl>,
## # `Body Mass Index (BMI)` <dbl>, `Total Body Water (TBW)` <dbl>,
## # `Extracellular Water (ECW)` <dbl>, `Intracellular Water (ICW)` <dbl>,
## # `Extracellular Fluid/Total Body Water (ECF/TBW)` <dbl>,
## # `Total Body Fat Ratio (TBFR) (%)` <dbl>, `Lean Mass (LM) (%)` <dbl>, …
str(data)
## tibble [319 × 39] (S3: tbl_df/tbl/data.frame)
## $ Gallstone Status : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Age : num [1:319] 50 47 61 41 42 96 37 41 38 38 ...
## $ Gender : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Comorbidity : num [1:319] 0 1 0 0 0 0 0 0 0 0 ...
## $ Coronary Artery Disease (CAD) : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Hypothyroidism : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Hyperlipidemia : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Diabetes Mellitus (DM) : num [1:319] 0 0 0 0 0 0 0 0 0 0 ...
## $ Height : num [1:319] 185 176 171 168 178 155 185 176 186 171 ...
## $ Weight : num [1:319] 92.8 94.5 91.1 67.7 89.6 49 67.1 114 93.7 68.6 ...
## $ Body Mass Index (BMI) : num [1:319] 27.1 30.5 31.2 24 28.3 20.4 19.6 36.8 27.1 23.5 ...
## $ Total Body Water (TBW) : num [1:319] 52.9 43.1 47.2 41.4 51.4 34 41.8 57.6 51.9 39.5 ...
## $ Extracellular Water (ECW) : num [1:319] 21.2 19.5 20.1 17 20 15.7 17.1 23.5 20.9 16.6 ...
## $ Intracellular Water (ICW) : num [1:319] 31.7 23.6 27.1 24.4 31.4 18.3 24.7 34.1 31 22.9 ...
## $ Extracellular Fluid/Total Body Water (ECF/TBW): num [1:319] 40 45 43 41 39 46 41 41 40 42 ...
## $ Total Body Fat Ratio (TBFR) (%) : num [1:319] 19.2 32.8 27.3 15.8 20 6.3 11.3 31.8 21.5 19.2 ...
## $ Lean Mass (LM) (%) : num [1:319] 80.8 67.2 72.7 84.2 80 ...
## $ Body Protein Content (Protein) (%) : num [1:319] 18.9 16.7 16.4 16.9 16.8 ...
## $ Visceral Fat Rating (VFR) : num [1:319] 9 15 15 6 8 12 3 16 8 6 ...
## $ Bone Mass (BM) : num [1:319] 3.7 3.2 3.3 2.9 3.5 2.4 3 3.8 3.6 2.8 ...
## $ Muscle Mass (MM) : num [1:319] 71.4 60.3 62.9 54.1 68.2 43.5 56.5 73.9 70 52.6 ...
## $ Obesity (%) : num [1:319] 23.4 38.8 41.7 9 28.6 7.4 10.9 67.4 23.1 6.7 ...
## $ Total Fat Content (TFC) : num [1:319] 17.8 31 24.9 10.7 17.9 3.1 7.6 36.3 20.1 13.2 ...
## $ Visceral Fat Area (VFA) : num [1:319] 10.6 18.4 16.2 6.5 10.4 0.9 4.6 23.7 12.7 8.2 ...
## $ Visceral Muscle Area (VMA) (Kg) : num [1:319] 39.7 32.7 34 29.2 37.4 25.9 31.4 37.5 37.8 28.8 ...
## $ Hepatic Fat Accumulation (HFA) : num [1:319] 0 0 0 1 2 0 0 3 2 0 ...
## $ Glucose : num [1:319] 102 94 103 69 109 74 94 125 93 93 ...
## $ Total Cholesterol (TC) : num [1:319] 250 172 179 173 205 133 166 246 290 239 ...
## $ Low Density Lipoprotein (LDL) : num [1:319] 175 108 124 73 154 ...
## $ High Density Lipoprotein (HDL) : num [1:319] 40 43 43 59 30 30 40 34 33 43 ...
## $ Triglyceride : num [1:319] 134 103 69 53 326 65 60 464 679 129 ...
## $ Aspartat Aminotransferaz (AST) : num [1:319] 20 14 18 20 27 13 15 26 68 19 ...
## $ Alanin Aminotransferaz (ALT) : num [1:319] 22 13 14 12 54 13 14 28 102 34 ...
## $ Alkaline Phosphatase (ALP) : num [1:319] 87 46 66 34 71 60 72 69 70 75 ...
## $ Creatinine : num [1:319] 0.82 0.87 1.25 1.02 0.82 1.46 0.77 1.3 0.91 0.91 ...
## $ Glomerular Filtration Rate (GFR) : num [1:319] 112.5 107.1 65.5 94.1 112.5 ...
## $ C-Reactive Protein (CRP) : num [1:319] 0 0 0 0 0 0 0 0.11 1.57 0 ...
## $ Hemoglobin (HGB) : num [1:319] 16 14.4 16.2 15.4 16.8 11 13.8 16.5 16.5 16.6 ...
## $ Vitamin D : num [1:319] 33 25 30.2 35.4 40.6 45.8 20 24.5 22.7 15.6 ...
data_selected <- data[, c(
'Age',
'Height',
'Weight',
'Body Mass Index (BMI)',
'Total Body Water (TBW)',
'Extracellular Water (ECW)',
'Intracellular Water (ICW)',
'Extracellular Fluid/Total Body Water (ECF/TBW)',
'Total Body Fat Ratio (TBFR) (%)',
'Lean Mass (LM) (%)',
'Body Protein Content (Protein) (%)',
'Visceral Fat Rating (VFR)',
'Bone Mass (BM)',
'Muscle Mass (MM)',
'Obesity (%)',
'Total Fat Content (TFC)',
'Visceral Fat Area (VFA)',
'Visceral Muscle Area (VMA) (Kg)',
'Glucose',
'Total Cholesterol (TC)',
'Low Density Lipoprotein (LDL)',
'High Density Lipoprotein (HDL)',
'Triglyceride',
'Aspartat Aminotransferaz (AST)',
'Alanin Aminotransferaz (ALT)',
'Alkaline Phosphatase (ALP)',
'Creatinine',
'Glomerular Filtration Rate (GFR)',
'C-Reactive Protein (CRP)',
'Hemoglobin (HGB)',
'Vitamin D'
)]
#rename variabel
colnames(data_selected) <- paste0("X", 1:ncol(data_selected))
head(data_selected)
## # A tibble: 6 × 31
## X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 50 185 92.8 27.1 52.9 21.2 31.7 40 19.2 80.8 18.9 9 3.7
## 2 47 176 94.5 30.5 43.1 19.5 23.6 45 32.8 67.2 16.7 15 3.2
## 3 61 171 91.1 31.2 47.2 20.1 27.1 43 27.3 72.7 16.4 15 3.3
## 4 41 168 67.7 24 41.4 17 24.4 41 15.8 84.2 16.9 6 2.9
## 5 42 178 89.6 28.3 51.4 20 31.4 39 20 80.0 16.8 8 3.5
## 6 96 155 49 20.4 34 15.7 18.3 46 6.3 93.7 18.5 12 2.4
## # ℹ 18 more variables: X14 <dbl>, X15 <dbl>, X16 <dbl>, X17 <dbl>, X18 <dbl>,
## # X19 <dbl>, X20 <dbl>, X21 <dbl>, X22 <dbl>, X23 <dbl>, X24 <dbl>,
## # X25 <dbl>, X26 <dbl>, X27 <dbl>, X28 <dbl>, X29 <dbl>, X30 <dbl>, X31 <dbl>
#correlation
cor(data_selected)
## X1 X2 X3 X4 X5
## X1 1.000000000 -0.307407233 0.040579150 0.235835013 -0.083262690
## X2 -0.307407233 1.000000000 0.411769384 -0.219450930 0.713265170
## X3 0.040579150 0.411769384 1.000000000 0.790874698 0.766921006
## X4 0.235835013 -0.219450930 0.790874698 1.000000000 0.335632016
## X5 -0.083262690 0.713265170 0.766921006 0.335632016 1.000000000
## X6 0.008023629 0.610825691 0.789365033 0.429647317 0.904350746
## X7 -0.198591514 0.739121391 0.686426634 0.234729831 0.817247287
## X8 0.326684923 -0.404556505 -0.055636656 0.211597804 -0.231735526
## X9 0.243447893 -0.528786690 0.374816764 0.753274685 -0.226242498
## X10 -0.243380721 0.531643020 -0.370677942 -0.752073024 0.232033640
## X11 0.029039752 0.419254991 -0.255477689 -0.550718075 0.084584916
## X12 0.531990810 0.080220086 0.763458030 0.748799372 0.555851726
## X13 -0.080666189 0.660764746 0.682284115 0.289732636 0.834346323
## X14 -0.101156772 0.765607903 0.772424360 0.308942274 0.928633383
## X15 0.045472562 -0.133613908 0.087556268 0.181664467 -0.002334898
## X16 0.195508109 -0.204243878 0.717435075 0.902706362 0.174362187
## X17 0.146932211 0.124302240 0.881509145 0.849625126 0.490523703
## X18 -0.056233430 0.711150281 0.714208930 0.290069818 0.842097173
## X19 0.148504261 0.030066314 0.139238971 0.125367744 0.121849410
## X20 0.159004883 -0.027024648 -0.005790833 0.004509984 -0.037914458
## X21 0.116586605 0.012359156 -0.023250461 -0.035787140 -0.005203587
## X22 0.103680532 -0.312972142 -0.250388889 -0.065000902 -0.382704574
## X23 0.058043251 0.236024572 0.311733847 0.173438727 0.325636932
## X24 -0.056929533 0.175510653 0.133568172 0.023173910 0.227864318
## X25 -0.060162568 0.248800185 0.227678492 0.070606821 0.322370687
## X26 0.121376404 -0.067962275 0.084705271 0.150627881 0.013636217
## X27 0.106189722 0.474618248 0.175979974 -0.131232080 0.466990731
## X28 -0.555640123 0.090786020 -0.043529120 -0.100273763 -0.015393012
## X29 -0.002826173 -0.101731775 0.049845881 0.141853099 -0.049769865
## X30 -0.121711032 0.601949463 0.304154099 -0.074216779 0.560095018
## X31 0.057598703 0.002872504 -0.085984914 -0.094750050 0.037904797
## X6 X7 X8 X9 X10 X11
## X1 0.008023629 -0.198591514 0.32668492 0.243447893 -0.243380721 0.02903975
## X2 0.610825691 0.739121391 -0.40455650 -0.528786690 0.531643020 0.41925499
## X3 0.789365033 0.686426634 -0.05563666 0.374816764 -0.370677942 -0.25547769
## X4 0.429647317 0.234729831 0.21159780 0.753274685 -0.752073024 -0.55071807
## X5 0.904350746 0.817247287 -0.23173553 -0.226242498 0.232033640 0.08458492
## X6 1.000000000 0.783681732 0.12412309 -0.097254712 0.103223004 -0.11337895
## X7 0.783681732 1.000000000 -0.39553651 -0.315013157 0.319642451 0.17897861
## X8 0.124123086 -0.395536511 1.00000000 0.397466128 -0.399562035 -0.53118074
## X9 -0.097254712 -0.315013157 0.39746613 1.000000000 -0.994054990 -0.67291852
## X10 0.103223004 0.319642451 -0.39956203 -0.994054990 1.000000000 0.67286230
## X11 -0.113378952 0.178978612 -0.53118074 -0.672918522 0.672862295 1.00000000
## X12 0.659615969 0.410034304 0.23256466 0.394664544 -0.392237713 -0.27703281
## X13 0.820540398 0.793775220 -0.18716221 -0.224419411 0.237617518 0.11101098
## X14 0.865197688 0.904088221 -0.31058698 -0.246536280 0.251265051 0.18649662
## X15 0.012884883 -0.013212906 0.03543015 0.161172057 -0.159559512 -0.14230976
## X16 0.279223712 0.075162209 0.25749939 0.866062462 -0.864811282 -0.61022076
## X17 0.567959607 0.395320118 0.13515001 0.651718915 -0.649354680 -0.50977870
## X18 0.767504412 0.802562424 -0.30384067 -0.203871648 0.210321942 0.21472516
## X19 0.128716189 0.086888406 0.01636131 0.048744685 -0.044243800 -0.01398388
## X20 -0.017373693 -0.057560942 0.07150033 0.078881627 -0.090184560 0.01987760
## X21 0.037368159 -0.015880805 0.10484708 -0.007487995 -0.002906991 0.04802210
## X22 -0.356704973 -0.373568525 0.11726820 0.195381347 -0.192898345 -0.09837113
## X23 0.285614788 0.314240184 -0.13439273 -0.013576566 0.006022450 0.06780448
## X24 0.227366879 0.211334573 -0.03645544 -0.115314188 0.118915119 0.04216347
## X25 0.306369665 0.328279168 -0.09664352 -0.126609582 0.127604585 0.05477681
## X26 0.017713942 -0.005741656 0.05106969 0.119358821 -0.135548573 -0.04728167
## X27 0.413714867 0.453888242 -0.18315728 -0.446410375 0.444089098 0.36284599
## X28 -0.030853256 0.046496958 -0.09372887 -0.084316126 0.083879992 -0.08038108
## X29 -0.075667938 -0.044564079 -0.05337014 0.159571895 -0.158278180 -0.11006863
## X30 0.538972805 0.602186352 -0.18058998 -0.402272877 0.402383350 0.21365243
## X31 0.084003860 0.011591064 0.12774425 -0.152076268 0.155425448 0.02911991
## X12 X13 X14 X15 X16
## X1 0.531990810 -0.080666189 -0.1011567725 0.045472562 0.19550811
## X2 0.080220086 0.660764746 0.7656079028 -0.133613908 -0.20424388
## X3 0.763458030 0.682284115 0.7724243604 0.087556268 0.71743508
## X4 0.748799372 0.289732636 0.3089422744 0.181664467 0.90270636
## X5 0.555851726 0.834346323 0.9286333834 -0.002334898 0.17436219
## X6 0.659615969 0.820540398 0.8651976881 0.012884883 0.27922371
## X7 0.410034304 0.793775220 0.9040882208 -0.013212906 0.07516221
## X8 0.232564663 -0.187162210 -0.3105869769 0.035430149 0.25749939
## X9 0.394664544 -0.224419411 -0.2465362797 0.161172057 0.86606246
## X10 -0.392237713 0.237617518 0.2512650511 -0.159559512 -0.86481128
## X11 -0.277032808 0.111010978 0.1864966151 -0.142309758 -0.61022076
## X12 1.000000000 0.475441698 0.5228714524 0.105388866 0.63426534
## X13 0.475441698 1.000000000 0.8399008967 0.003024776 0.14030397
## X14 0.522871452 0.839900897 1.0000000000 -0.013387926 0.15995214
## X15 0.105388866 0.003024776 -0.0133879259 1.000000000 0.15268472
## X16 0.634265339 0.140303967 0.1599521436 0.152684716 1.00000000
## X17 0.805343334 0.414058170 0.4743802747 0.117578637 0.87362806
## X18 0.457868320 0.755827266 0.8648827026 -0.026295568 0.15427361
## X19 0.228618856 0.144522705 0.1160794129 0.114104002 0.10095044
## X20 0.035993110 -0.035398265 -0.0451610926 -0.015660110 0.02646869
## X21 0.022154451 0.032705401 0.0018718626 -0.028416874 -0.04291551
## X22 -0.163646598 -0.344326519 -0.3789497143 0.011608801 0.03890891
## X23 0.246040178 0.294357852 0.3386705395 0.023143165 0.11371526
## X24 0.103385712 0.186209158 0.2274269031 0.024772183 -0.03273613
## X25 0.170082166 0.260295186 0.3280774185 0.014200298 0.01211940
## X26 0.125174004 -0.023465500 -0.0007595401 -0.003236782 0.12672650
## X27 0.224227732 0.419776095 0.4693825698 -0.048299265 -0.24824601
## X28 -0.308161450 -0.009193478 -0.0015389385 -0.018759627 -0.07087217
## X29 0.019130370 -0.065895304 -0.0569800320 0.009651578 0.13660236
## X30 0.236223547 0.524228276 0.5730241284 -0.024880262 -0.17355510
## X31 0.002308791 0.055387654 -0.0009158647 -0.089796464 -0.15809902
## X17 X18 X19 X20 X21
## X1 0.1469322106 -0.0562334304 0.148504261 0.159004883 0.116586605
## X2 0.1243022402 0.7111502810 0.030066314 -0.027024648 0.012359156
## X3 0.8815091446 0.7142089304 0.139238971 -0.005790833 -0.023250461
## X4 0.8496251264 0.2900698182 0.125367744 0.004509984 -0.035787140
## X5 0.4905237027 0.8420971732 0.121849410 -0.037914458 -0.005203587
## X6 0.5679596072 0.7675044117 0.128716189 -0.017373693 0.037368159
## X7 0.3953201180 0.8025624243 0.086888406 -0.057560942 -0.015880805
## X8 0.1351500093 -0.3038406651 0.016361315 0.071500328 0.104847081
## X9 0.6517189147 -0.2038716480 0.048744685 0.078881627 -0.007487995
## X10 -0.6493546804 0.2103219425 -0.044243800 -0.090184560 -0.002906991
## X11 -0.5097786957 0.2147251585 -0.013983879 0.019877596 0.048022105
## X12 0.8053433343 0.4578683201 0.228618856 0.035993110 0.022154451
## X13 0.4140581702 0.7558272660 0.144522705 -0.035398265 0.032705401
## X14 0.4743802747 0.8648827026 0.116079413 -0.045161093 0.001871863
## X15 0.1175786366 -0.0262955679 0.114104002 -0.015660110 -0.028416874
## X16 0.8736280622 0.1542736134 0.100950440 0.026468687 -0.042915513
## X17 1.0000000000 0.4092064197 0.147728513 0.015861710 -0.030169431
## X18 0.4092064197 1.0000000000 0.110376182 -0.029266349 -0.001514025
## X19 0.1477285130 0.1103761824 1.000000000 0.083041839 0.042791632
## X20 0.0158617105 -0.0292663487 0.083041839 1.000000000 0.865820707
## X21 -0.0301694312 -0.0015140253 0.042791632 0.865820707 1.000000000
## X22 -0.0941501707 -0.3740297996 -0.113648952 0.200755658 0.040132187
## X23 0.2034627989 0.3551423516 0.340377678 0.326705964 0.157004007
## X24 0.0495486926 0.2249583652 -0.046717523 0.009091761 0.052955525
## X25 0.1163813898 0.3069301853 -0.005581735 0.008064127 0.041409491
## X26 0.1066218367 -0.0001625898 0.190717890 0.043266813 0.062633753
## X27 -0.0006752588 0.4241640796 0.104070277 0.042102837 0.046206274
## X28 -0.0946379243 -0.0293840783 -0.139885170 -0.040048309 0.017354387
## X29 0.0982660275 -0.0383707814 -0.039604655 -0.047929075 -0.051556942
## X30 0.1250776011 0.5109146787 0.140698964 0.087683057 0.109977012
## X31 -0.1175522360 -0.0110560591 -0.036566305 -0.007823704 0.037148599
## X22 X23 X24 X25 X26
## X1 0.10368053 0.05804325 -0.056929533 -0.060162568 0.1213764043
## X2 -0.31297214 0.23602457 0.175510653 0.248800185 -0.0679622752
## X3 -0.25038889 0.31173385 0.133568172 0.227678492 0.0847052710
## X4 -0.06500090 0.17343873 0.023173910 0.070606821 0.1506278811
## X5 -0.38270457 0.32563693 0.227864318 0.322370687 0.0136362170
## X6 -0.35670497 0.28561479 0.227366879 0.306369665 0.0177139419
## X7 -0.37356853 0.31424018 0.211334573 0.328279168 -0.0057416561
## X8 0.11726820 -0.13439273 -0.036455441 -0.096643518 0.0510696862
## X9 0.19538135 -0.01357657 -0.115314188 -0.126609582 0.1193588205
## X10 -0.19289834 0.00602245 0.118915119 0.127604585 -0.1355485726
## X11 -0.09837113 0.06780448 0.042163467 0.054776810 -0.0472816658
## X12 -0.16364660 0.24604018 0.103385712 0.170082166 0.1251740039
## X13 -0.34432652 0.29435785 0.186209158 0.260295186 -0.0234655002
## X14 -0.37894971 0.33867054 0.227426903 0.328077418 -0.0007595401
## X15 0.01160880 0.02314317 0.024772183 0.014200298 -0.0032367820
## X16 0.03890891 0.11371526 -0.032736135 0.012119397 0.1267265004
## X17 -0.09415017 0.20346280 0.049548693 0.116381390 0.1066218367
## X18 -0.37402980 0.35514235 0.224958365 0.306930185 -0.0001625898
## X19 -0.11364895 0.34037768 -0.046717523 -0.005581735 0.1907178897
## X20 0.20075566 0.32670596 0.009091761 0.008064127 0.0432668125
## X21 0.04013219 0.15700401 0.052955525 0.041409491 0.0626337530
## X22 1.00000000 -0.35112695 -0.105746106 -0.101853547 -0.0491465926
## X23 -0.35112695 1.00000000 0.103122037 0.138107417 0.0790058737
## X24 -0.10574611 0.10312204 1.000000000 0.853426204 0.0490453987
## X25 -0.10185355 0.13810742 0.853426204 1.000000000 0.1426247975
## X26 -0.04914659 0.07900587 0.049045399 0.142624798 1.0000000000
## X27 -0.26022337 0.22548491 0.091605778 0.158613100 -0.0159390858
## X28 -0.05227722 -0.06208019 0.078518055 0.047248247 -0.0765925253
## X29 0.02891611 -0.03574297 -0.070266206 -0.063544499 0.0656930436
## X30 -0.29737691 0.32138847 0.209008480 0.280928254 0.0248535651
## X31 -0.01653378 -0.08473394 0.029499171 -0.033706971 -0.0818522490
## X27 X28 X29 X30 X31
## X1 0.1061897221 -0.555640123 -0.002826173 -0.12171103 0.0575987035
## X2 0.4746182485 0.090786020 -0.101731775 0.60194946 0.0028725042
## X3 0.1759799737 -0.043529120 0.049845881 0.30415410 -0.0859849135
## X4 -0.1312320805 -0.100273763 0.141853099 -0.07421678 -0.0947500504
## X5 0.4669907307 -0.015393012 -0.049769865 0.56009502 0.0379047971
## X6 0.4137148671 -0.030853256 -0.075667938 0.53897281 0.0840038603
## X7 0.4538882421 0.046496958 -0.044564079 0.60218635 0.0115910640
## X8 -0.1831572789 -0.093728873 -0.053370142 -0.18058998 0.1277442533
## X9 -0.4464103750 -0.084316126 0.159571895 -0.40227288 -0.1520762679
## X10 0.4440890976 0.083879992 -0.158278180 0.40238335 0.1554254479
## X11 0.3628459932 -0.080381075 -0.110068631 0.21365243 0.0291199140
## X12 0.2242277325 -0.308161450 0.019130370 0.23622355 0.0023087907
## X13 0.4197760952 -0.009193478 -0.065895304 0.52422828 0.0553876539
## X14 0.4693825698 -0.001538938 -0.056980032 0.57302413 -0.0009158647
## X15 -0.0482992647 -0.018759627 0.009651578 -0.02488026 -0.0897964643
## X16 -0.2482460081 -0.070872171 0.136602363 -0.17355510 -0.1580990185
## X17 -0.0006752588 -0.094637924 0.098266028 0.12507760 -0.1175522360
## X18 0.4241640796 -0.029384078 -0.038370781 0.51091468 -0.0110560591
## X19 0.1040702765 -0.139885170 -0.039604655 0.14069896 -0.0365663047
## X20 0.0421028365 -0.040048309 -0.047929075 0.08768306 -0.0078237039
## X21 0.0462062738 0.017354387 -0.051556942 0.10997701 0.0371485988
## X22 -0.2602233689 -0.052277216 0.028916113 -0.29737691 -0.0165337827
## X23 0.2254849082 -0.062080192 -0.035742972 0.32138847 -0.0847339416
## X24 0.0916057776 0.078518055 -0.070266206 0.20900848 0.0294991709
## X25 0.1586131005 0.047248247 -0.063544499 0.28092825 -0.0337069708
## X26 -0.0159390858 -0.076592525 0.065693044 0.02485357 -0.0818522490
## X27 1.0000000000 -0.473715710 -0.049009646 0.50054576 0.0920674533
## X28 -0.4737157095 1.000000000 -0.145863868 -0.02462084 -0.0666329001
## X29 -0.0490096457 -0.145863868 1.000000000 -0.18244866 -0.0512353512
## X30 0.5005457600 -0.024620844 -0.182448657 1.00000000 0.0331871716
## X31 0.0920674533 -0.066632900 -0.051235351 0.03318717 1.0000000000
#cek MSA
r <- cor(data_selected)
KMO(r)
## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = r)
## Overall MSA = 0.8
## MSA for each item =
## X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16
## 0.55 0.79 0.80 0.78 0.82 0.77 0.83 0.48 0.86 0.84 0.83 0.79 0.97 0.97 0.86 0.91
## X17 X18 X19 X20 X21 X22 X23 X24 X25 X26 X27 X28 X29 X30 X31
## 0.83 0.98 0.73 0.40 0.40 0.68 0.65 0.60 0.66 0.52 0.87 0.59 0.58 0.94 0.78
#delete X21
data_selected = data_selected[-21]
#delete X20
data_selected = data_selected[-20]
#delete X8
data_selected = data_selected[-8]
#Bartlett Test
bartlett.test(data_selected)
##
## Bartlett test of homogeneity of variances
##
## data: data_selected
## Bartlett's K-squared = 23859, df = 27, p-value < 2.2e-16
cortest.bartlett(data_selected)
## R was not square, finding R from data
## $chisq
## [1] 11464.99
##
## $p.value
## [1] 0
##
## $df
## [1] 378
# scale data
scale_data = scale(data_selected)
r = cov(scale_data)
pca_test <- prcomp(scale(data_selected))
ncol(pca_test$rotation)
## [1] 28
pca_result <- PCA(scale_data,
scale.unit = TRUE,
graph = FALSE,
ncp=ncol(data_selected))
# summary pca result
pca_result$eig # vs print(cumvar)
## eigenvalue percentage of variance cumulative percentage of variance
## comp 1 8.543073251 30.51097590 30.51098
## comp 2 5.997211454 21.41861234 51.92959
## comp 3 2.079356763 7.42627415 59.35586
## comp 4 1.680595002 6.00212501 65.35799
## comp 5 1.361421570 4.86221989 70.22021
## comp 6 1.095594692 3.91283819 74.13305
## comp 7 1.004695884 3.58819959 77.72125
## comp 8 0.940160496 3.35771606 81.07896
## comp 9 0.868754785 3.10269566 84.18166
## comp 10 0.748523584 2.67329851 86.85496
## comp 11 0.693103127 2.47536831 89.33032
## comp 12 0.563403894 2.01215677 91.34248
## comp 13 0.495751983 1.77054280 93.11302
## comp 14 0.394491704 1.40889894 94.52192
## comp 15 0.289539655 1.03407020 95.55599
## comp 16 0.253543051 0.90551090 96.46150
## comp 17 0.214527841 0.76617086 97.22767
## comp 18 0.197741174 0.70621848 97.93389
## comp 19 0.152630634 0.54510941 98.47900
## comp 20 0.126883650 0.45315589 98.93216
## comp 21 0.092012148 0.32861482 99.26077
## comp 22 0.065127393 0.23259783 99.49337
## comp 23 0.056686287 0.20245103 99.69582
## comp 24 0.039480384 0.14100137 99.83682
## comp 25 0.021525474 0.07687669 99.91370
## comp 26 0.014970573 0.05346633 99.96717
## comp 27 0.005408096 0.01931463 99.98648
## comp 28 0.003785450 0.01351946 100.00000
# scree plot
fviz_eig(pca_result,
addlabels = TRUE,
ncp = ncol(data_selected),
barfill = "skyblue",
barcolor = "darkblue",
linecolor = "red")
## Warning in geom_bar(stat = "identity", fill = barfill, color = barcolor, :
## Ignoring empty aesthetic: `width`.
#Biplot
fviz_pca_biplot(pca_result,
geom.ind = "point",
#col.ind = status.ipm,
#palette = c("#FC4E07","#E7B800", "#00AFBB"),
addEllipses = TRUE,
#legend.title = "Kategori"
)
# correlation circle
contrib_circle <- fviz_pca_var(pca_result, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) +
ggtitle("Kontribusi Variabel")
## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## ℹ The deprecated feature was likely used in the factoextra package.
## Please report the issue at <https://github.com/kassambara/factoextra/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## ℹ The deprecated feature was likely used in the factoextra package.
## Please report the issue at <https://github.com/kassambara/factoextra/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
plot(contrib_circle)
pca_final <- principal(data_selected,
nfactors = 7,
rotate = "none")
print(pca_final$loadings, cutoff = 0.4)
##
## Loadings:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## X1 0.751
## X2 0.689 -0.538
## X3 0.866 0.449
## X4 0.462 0.837
## X5 0.936
## X6 0.922
## X7 0.879
## X9 0.963
## X10 -0.963
## X11 -0.723
## X12 0.673 0.535
## X13 0.864
## X14 0.945
## X15 0.748
## X16 0.905
## X17 0.627 0.719
## X18 0.875
## X19 0.613
## X22 -0.424
## X23 0.423 0.576
## X24 0.847
## X25 0.830
## X26
## X27 0.481 -0.419 0.509
## X28 -0.821
## X29 0.758
## X30 0.610
## X31 -0.417 -0.446 -0.451
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## SS loadings 8.543 5.997 2.079 1.681 1.361 1.096 1.005
## Proportion Var 0.305 0.214 0.074 0.060 0.049 0.039 0.036
## Cumulative Var 0.305 0.519 0.594 0.654 0.702 0.741 0.777
pca_rot <- principal(data_selected,
nfactors = 7,
rotate = "varimax")
print(pca_rot$loadings, cutoff = 0.4)
##
## Loadings:
## RC1 RC2 RC3 RC4 RC5 RC6 RC7
## X1 0.816
## X2 0.813
## X3 0.753 0.626
## X4 0.906
## X5 0.938
## X6 0.888
## X7 0.915
## X9 0.914
## X10 -0.912
## X11 -0.747
## X12 0.494 0.617 0.473
## X13 0.880
## X14 0.960
## X15 0.820
## X16 0.948
## X17 0.458 0.832
## X18 0.883
## X19 0.712
## X22 -0.402 -0.438
## X23 0.676
## X24 0.934
## X25 0.926
## X26 0.516
## X27 0.531 0.505
## X28 -0.876
## X29 0.754
## X30 0.632
## X31 -0.557 -0.492
##
## RC1 RC2 RC3 RC4 RC5 RC6 RC7
## SS loadings 8.010 5.939 2.102 1.885 1.612 1.143 1.071
## Proportion Var 0.286 0.212 0.075 0.067 0.058 0.041 0.038
## Cumulative Var 0.286 0.498 0.573 0.641 0.698 0.739 0.777
#Factor analysis
fa <- principal(scale_data, nfactors = 7, rotate = "none")
fa
## Principal Components Analysis
## Call: principal(r = scale_data, nfactors = 7, rotate = "none")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 h2 u2 com
## X1 -0.01 0.33 0.75 0.21 -0.16 -0.11 0.01 0.75 0.246 1.7
## X2 0.69 -0.54 -0.13 -0.15 -0.01 0.11 0.03 0.82 0.181 2.2
## X3 0.87 0.45 -0.10 -0.10 -0.04 0.05 0.01 0.98 0.025 1.6
## X4 0.46 0.84 -0.03 0.00 -0.03 0.00 -0.02 0.92 0.084 1.6
## X5 0.94 -0.13 -0.04 -0.08 -0.07 0.00 0.00 0.90 0.095 1.1
## X6 0.92 0.01 -0.03 -0.05 -0.12 -0.11 -0.04 0.88 0.119 1.1
## X7 0.88 -0.24 -0.12 -0.10 -0.02 0.06 0.03 0.86 0.142 1.2
## X9 -0.09 0.96 -0.06 0.01 0.02 0.01 -0.02 0.94 0.060 1.0
## X10 0.09 -0.96 0.06 -0.02 -0.03 -0.01 0.02 0.94 0.058 1.0
## X11 0.03 -0.72 0.27 0.01 0.02 0.15 0.08 0.63 0.373 1.4
## X12 0.67 0.54 0.33 0.08 -0.12 -0.11 -0.01 0.88 0.121 2.6
## X13 0.86 -0.15 -0.04 -0.12 -0.06 -0.04 0.02 0.79 0.212 1.1
## X14 0.94 -0.17 -0.06 -0.09 -0.05 0.05 0.03 0.94 0.062 1.1
## X15 0.03 0.21 0.00 0.09 0.22 -0.22 0.75 0.71 0.293 1.6
## X16 0.32 0.90 -0.10 -0.04 -0.01 0.03 -0.01 0.93 0.066 1.3
## X17 0.63 0.72 -0.06 -0.06 -0.05 0.01 0.00 0.92 0.079 2.0
## X18 0.88 -0.15 -0.03 -0.07 -0.02 0.08 0.02 0.80 0.197 1.1
## X19 0.19 0.10 0.34 0.05 0.61 -0.20 -0.06 0.59 0.415 2.2
## X22 -0.42 0.18 0.00 0.06 -0.35 0.03 0.22 0.39 0.610 3.0
## X23 0.42 -0.01 0.17 0.07 0.58 -0.06 -0.10 0.56 0.441 2.2
## X24 0.28 -0.14 -0.27 0.85 -0.12 -0.01 0.01 0.90 0.097 1.5
## X25 0.38 -0.13 -0.24 0.83 -0.08 0.06 0.02 0.92 0.077 1.7
## X26 0.06 0.16 0.15 0.31 0.37 0.29 -0.37 0.51 0.493 4.6
## X27 0.48 -0.42 0.51 0.02 -0.11 0.09 0.11 0.70 0.303 3.2
## X28 -0.07 -0.12 -0.82 -0.12 0.21 -0.17 -0.11 0.79 0.206 1.4
## X29 -0.05 0.20 0.05 -0.08 -0.08 0.76 0.00 0.63 0.369 1.2
## X30 0.61 -0.40 0.06 0.05 0.12 -0.13 0.02 0.57 0.434 2.0
## X31 0.00 -0.15 0.15 -0.02 -0.42 -0.45 -0.45 0.62 0.379 3.4
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## SS loadings 8.54 6.00 2.08 1.68 1.36 1.10 1.00
## Proportion Var 0.31 0.21 0.07 0.06 0.05 0.04 0.04
## Cumulative Var 0.31 0.52 0.59 0.65 0.70 0.74 0.78
## Proportion Explained 0.39 0.28 0.10 0.08 0.06 0.05 0.05
## Cumulative Proportion 0.39 0.67 0.76 0.84 0.90 0.95 1.00
##
## Mean item complexity = 1.8
## Test of the hypothesis that 7 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.03
## with the empirical chi square 255.28 with prob < 0.0075
##
## Fit based upon off diagonal values = 0.99
# Factor Analysis with rotation varimax
fa_1 <- principal(scale_data,
nfactors = 7,
rotate = "varimax")
print(fa_1$loadings, cutoff = 0.4, sort = TRUE)
##
## Loadings:
## RC1 RC2 RC3 RC4 RC5 RC6 RC7
## X2 0.813
## X3 0.753 0.626
## X5 0.938
## X6 0.888
## X7 0.915
## X13 0.880
## X14 0.960
## X18 0.883
## X27 0.531 0.505
## X30 0.632
## X4 0.906
## X9 0.914
## X10 -0.912
## X11 -0.747
## X12 0.494 0.617 0.473
## X16 0.948
## X17 0.458 0.832
## X1 0.816
## X28 -0.876
## X24 0.934
## X25 0.926
## X19 0.712
## X23 0.676
## X26 0.516
## X29 0.754
## X31 -0.557 -0.492
## X15 0.820
## X22 -0.402 -0.438
##
## RC1 RC2 RC3 RC4 RC5 RC6 RC7
## SS loadings 8.010 5.939 2.102 1.885 1.612 1.143 1.071
## Proportion Var 0.286 0.212 0.075 0.067 0.058 0.041 0.038
## Cumulative Var 0.286 0.498 0.573 0.641 0.698 0.739 0.777
# scores FA
scores_FA = scale_data %*% solve(cor(scale_data)) %*% as.matrix(fa$loadings)
scores_FA
## PC1 PC2 PC3 PC4 PC5
## [1,] 1.296914422 -1.119446258 -0.175496501 -0.749934148 -0.410136947
## [2,] 0.667983992 0.407490153 -0.125629183 -0.998085390 -0.852560076
## [3,] 1.008745718 -0.036613442 1.920282640 -0.371531465 -1.529775043
## [4,] -0.282550233 -1.349724793 0.258387655 -0.638142778 -1.718698324
## [5,] 1.235211557 -1.041563953 -0.462046429 0.044326675 0.341930162
## [6,] -0.997248268 -1.590267009 4.574414254 0.617199233 -2.458068031
## [7,] -0.244620441 -1.952703370 -0.667358160 -0.875639150 0.114602986
## [8,] 2.394117051 0.619258978 0.880919383 -0.443245194 0.532399123
## [9,] 1.765604307 -1.107348975 -0.895285720 2.100207317 1.767992663
## [10,] -0.199617003 -1.145890795 -0.315903715 -0.003246369 0.444151274
## [11,] 1.319517324 0.220608317 -1.456943363 -0.517684864 -0.254238321
## [12,] 0.220526868 -1.211225490 -0.148734617 -0.051939386 0.618374382
## [13,] 0.309349635 -1.790664462 -0.784042003 -0.655243975 0.205175502
## [14,] 0.001879174 -2.295904787 0.907293617 -0.193208905 0.150109172
## [15,] -0.219279029 -1.177941566 0.897751839 -0.156846922 -0.296714405
## [16,] 0.574792257 -0.059231724 0.484075012 -0.727782611 -2.049554860
## [17,] 1.170818592 -0.817922914 0.502636975 -0.925743140 -0.883046317
## [18,] 1.381823306 -0.065157227 -0.640234840 -1.145235845 -1.148065497
## [19,] 1.446291654 -0.364479197 0.631511347 -0.333559113 -0.306790308
## [20,] 0.028867570 -1.904739622 -0.073186227 -0.800077730 -0.490939936
## [21,] 2.322905520 0.726374618 1.112039889 -0.052102151 5.350430173
## [22,] -0.005140317 -0.754509682 0.332981454 -0.331400845 -0.449920609
## [23,] 0.825052031 -0.613136121 0.548121170 -0.488063896 -0.601549501
## [24,] 3.333713702 3.016208648 -0.341547378 -0.306233167 -1.975458180
## [25,] 1.674660093 -0.371097455 -0.568392586 0.450525696 -0.238994005
## [26,] 0.918548742 -0.163469521 1.319900617 -0.031407484 -0.873158568
## [27,] 1.047789097 0.427715858 -0.001938533 -0.668179459 -0.195856984
## [28,] 1.807815004 -1.251713718 0.786015335 1.055168494 -0.606731536
## [29,] 0.945892035 0.181996641 2.386030587 0.065637626 -0.853288793
## [30,] 0.580337247 -0.645939990 0.558725115 -0.678926240 -1.096201045
## [31,] 1.278102140 -0.480855162 0.219929868 -0.705939285 -0.336838311
## [32,] 0.625424338 0.002430206 0.540326108 -0.157416422 -0.566199409
## [33,] 1.291984285 -0.196315602 -0.421075559 0.124832131 -0.411743877
## [34,] 0.717048208 -0.633195568 0.462014585 -0.086062482 -0.985434746
## [35,] 0.279195129 -0.698474151 0.409250323 0.217066166 -0.428541967
## [36,] -0.339616132 -1.110522978 0.697687842 -0.281208371 -0.151097374
## [37,] 1.927379977 -0.063825887 1.087888395 -0.261563726 0.095786210
## [38,] -0.142048081 -1.493173456 -0.448637711 -0.713231565 -0.137414054
## [39,] -0.052205293 -1.545164408 0.334642262 0.154639935 0.004395783
## [40,] -0.484092901 -0.426783553 2.879739162 0.416388506 -1.362336250
## [41,] 0.369740258 -0.701068165 1.893400502 -0.054325383 5.433812425
## [42,] 0.718165025 -1.498133557 1.656826603 -0.220473727 -1.365095829
## [43,] 0.502534802 -0.311268050 -0.065725902 0.181853710 -0.126385375
## [44,] 0.362423587 -0.977282221 0.870650943 0.147593743 -0.450237355
## [45,] 1.165944186 -0.729040140 -1.877090951 3.963742804 -1.343469802
## [46,] 0.380720533 -1.396345778 -1.590718520 0.073070103 -0.384809455
## [47,] 0.495801156 -1.469777310 -1.175890330 0.181203833 0.435390902
## [48,] 0.205877247 -0.761086932 1.987344121 1.609349851 -0.649593585
## [49,] -0.062617242 -0.496857203 0.543557875 0.408715096 0.407218316
## [50,] 1.660069421 -1.350777728 -0.332353789 0.583819835 0.977748326
## [51,] 0.862200939 -0.598780285 -0.167599263 0.375317934 2.428290500
## [52,] -0.238774418 -1.553002851 -0.806847373 -0.753485053 -0.534550621
## [53,] -0.584494072 0.206044731 -0.434549446 -0.337857723 0.016752333
## [54,] 1.190720387 -0.319123339 -0.669899112 1.548791071 -0.937205918
## [55,] 0.046030181 1.097454644 0.679756921 -0.094599505 -0.890734029
## [56,] -0.831978748 0.278790358 -0.096535968 -0.063326068 -0.562142076
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## [183,] 0.590131747 0.126832663 0.717585680 1.476658896 -0.328286624
## [184,] 0.991298304 -0.845603380 -0.081158537 -0.970567716 -0.309993527
## [185,] -0.688748024 0.794862706 2.395641755 0.565078158 -0.912921456
## [186,] -0.490277830 -1.787911604 -0.726480992 -0.223638128 -0.216473122
## [187,] 0.811223447 -0.336490358 0.429262593 0.386537029 0.198880391
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## [189,] -0.709384290 0.935437363 0.083973041 0.083575294 0.586362214
## [190,] 1.282502857 0.036046626 0.120118325 -0.623742070 0.445346106
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## [194,] -0.422818428 1.523665405 0.577771797 0.338107312 1.530221897
## [195,] 2.035645059 0.906986540 1.266529281 -0.388574032 -1.224431914
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## [198,] -0.151993199 -1.177610563 -1.167692843 2.330728693 0.706519475
## [199,] 0.099363834 -1.245289982 -0.049214974 -0.552162897 0.429027422
## [200,] 2.284355216 0.907662494 -0.904682805 -0.589100575 0.774885534
## [201,] 1.633812686 1.757742869 0.967493964 1.376409619 0.341196370
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## [262,] -2.402270786 -0.235734863 -0.996043497 0.324948672 0.491995741
## [263,] -0.492560502 1.825117095 0.249016556 0.936087717 -0.276571017
## [264,] 0.593968762 0.156271270 1.343080867 -0.021600428 -1.027861957
## [265,] 0.416187978 -0.937458855 0.303590243 -0.634800681 -0.402147177
## [266,] 0.135884898 0.959963948 -1.185642298 -0.608216615 0.800761964
## [267,] 0.906596551 0.292090590 -0.860286479 0.728500672 0.112688979
## [268,] 0.375112765 -0.586182389 -0.916065314 -0.253669220 0.087064795
## [269,] -0.280822358 1.987959628 -1.476451519 -1.110285017 -1.037464950
## [270,] -1.618689240 -0.625375209 -0.799301613 -0.827741942 -0.125924845
## [271,] -0.141259206 -0.385721465 0.178491643 -0.187369748 -0.291518619
## [272,] 1.076054456 -0.210949144 0.703046873 -0.130928496 0.500787514
## [273,] -0.695823637 2.212674618 2.497756928 -0.132615967 -2.686366038
## [274,] -0.680070062 0.965281013 -0.387060363 0.174770721 0.335857737
## [275,] 0.112777884 -1.411853534 -0.193850438 -0.442790220 0.130691176
## [276,] -0.870284045 0.774681325 -0.683216631 0.192532804 0.518253946
## [277,] -0.613702589 0.862302950 0.406441409 0.518021493 0.152361463
## [278,] -0.610403129 -1.293170144 2.775670745 -0.168428246 -1.035902083
## [279,] 1.817620991 -0.869665377 -3.201147013 11.390097363 -0.772412959
## [280,] -0.071385933 0.764359039 -1.408192386 -1.092185662 1.088768234
## [281,] 0.286112087 3.453205295 -0.488705383 -0.522089764 -0.950165971
## [282,] 0.399483485 -0.432416545 0.334569019 0.371340812 0.268396471
## [283,] -0.006217834 1.156435152 0.528893656 0.703557438 1.702409244
## [284,] -0.207776904 0.315377707 -1.001225019 -0.814075649 0.115230376
## [285,] -0.368730288 0.695566586 1.244479070 -0.109715603 -0.290146567
## [286,] 0.807375660 -0.565684184 0.200197980 0.028153451 1.378244904
## [287,] -0.513932521 1.124437624 -0.368906247 -0.082510986 0.542962537
## [288,] 0.891003758 -0.948285819 -1.880823261 -1.130301822 0.720012966
## [289,] -0.171035518 1.727279047 -0.041847005 -0.235594211 0.075728862
## [290,] -0.316687121 0.375555492 -0.912325958 -0.634563204 0.704864014
## [291,] 1.520616697 1.011031528 -0.128964549 -0.921943089 -0.848609616
## [292,] -1.334786098 0.486085807 1.154481632 0.741786646 -0.477801595
## [293,] -1.438034939 0.694774043 0.573304174 0.091491863 -1.011278935
## [294,] 2.157593714 1.935226231 -0.333360669 -0.730438464 -0.827892488
## [295,] 0.135245187 -1.004980526 1.191340929 -0.081375051 1.080387934
## [296,] -0.397015614 0.116928154 0.113916834 -0.394549850 1.192496981
## [297,] -0.618334158 0.688958745 -0.414164145 -0.291166729 -0.428221325
## [298,] 0.069046980 1.526976199 -0.258448568 -0.138952222 -0.359547489
## [299,] 0.007436525 0.655013252 -1.013852976 -0.396753354 -0.430821501
## [300,] 0.349953479 -0.621257031 2.155067318 -0.017262223 -1.143475199
## [301,] -1.611420481 0.427662589 1.563441756 0.581584188 0.325625906
## [302,] -0.875697227 0.571844049 -1.287440408 -0.492664411 0.404027012
## [303,] -1.584180467 0.612487520 0.121910256 0.319521323 -0.498923728
## [304,] 0.347580794 1.587798583 0.095724654 0.514407466 0.498066210
## [305,] 0.071804268 -1.071219533 1.338761609 -0.475271414 -1.049285357
## [306,] -0.618667992 1.146897009 2.278632430 0.822861867 -0.390578620
## [307,] -0.317533199 0.375260303 0.741597604 -0.193703240 1.067089797
## [308,] -0.443878105 0.312335660 -0.038797630 -0.505692630 0.473107465
## [309,] 0.968074374 0.343530444 2.092712304 0.162215944 -1.262350648
## [310,] 1.643539099 0.275866101 -0.263109550 -0.167599819 -0.796067435
## [311,] 1.170408201 -0.328100123 1.047416393 -0.671297706 2.358862997
## [312,] -1.147200014 -0.206086270 -0.656670203 -0.049378999 0.388523777
## [313,] 0.958265800 -0.424224236 2.741748614 0.649074674 3.391652415
## [314,] -0.893407064 1.228614007 -0.060932896 0.366359394 -0.313453679
## [315,] 0.907378529 -0.372380176 0.190284633 0.388921342 -0.071846996
## [316,] -1.803499608 -0.658735303 -1.527892578 -0.151311692 0.004609090
## [317,] 1.248801718 0.296607991 1.085224892 -0.001561455 -0.076632669
## [318,] 1.086316993 -0.890008153 -0.032354613 0.245755316 0.394832064
## [319,] -1.722230340 0.521374225 1.024328068 2.116264384 -4.336835068
## PC6 PC7
## [1,] -0.278449687 -0.6334381763
## [2,] -0.636213908 0.2666939614
## [3,] -0.393105540 0.3409889859
## [4,] -0.837830551 0.3616186616
## [5,] -1.034688471 -1.1153146667
## [6,] -0.880880709 -0.3323531885
## [7,] 0.325497160 0.0850999200
## [8,] -0.413643981 0.0478612249
## [9,] 0.081351470 -0.4885413814
## [10,] 0.113718067 0.1321971247
## [11,] -0.289648890 0.1397298986
## [12,] -0.013894458 -0.5401835367
## [13,] 0.354876042 0.2004148014
## [14,] 0.121507482 -0.7827654136
## [15,] -0.928123517 -1.0433937675
## [16,] -2.073074127 -0.5360063305
## [17,] -1.002142349 -0.5454860126
## [18,] -1.019333064 -0.0658049741
## [19,] -0.652557264 0.1741066072
## [20,] 0.097807471 0.7321724508
## [21,] -1.232376655 -0.8589157739
## [22,] -0.103962878 -0.2682322369
## [23,] 0.055039532 -0.0654730661
## [24,] -1.483110812 0.3715489427
## [25,] -0.725440456 -0.2711939426
## [26,] -0.521944973 0.8408603581
## [27,] -0.813941224 0.0203848401
## [28,] 0.232945540 0.6253716101
## [29,] -0.340301624 0.1291640063
## [30,] -0.550820534 0.5031184631
## [31,] -0.199651588 -0.0491192499
## [32,] -0.285615944 0.0496153456
## [33,] -0.064468434 -0.6559406114
## [34,] -0.150098271 -0.0090726208
## [35,] -1.057834405 -0.0933301902
## [36,] -0.669712743 -0.5642290784
## [37,] 0.063817822 -0.4280170367
## [38,] -0.114231301 0.0313690888
## [39,] 0.196904178 -0.2654589102
## [40,] -0.110004215 -0.3480587794
## [41,] -1.670040046 -2.1314505543
## [42,] -0.832102253 0.6946917472
## [43,] -0.821039642 -0.4230885185
## [44,] 0.448100111 -0.8252933916
## [45,] -0.689099937 0.3109635688
## [46,] 0.086175408 -0.2182505577
## [47,] -0.296319016 -0.4176732625
## [48,] -0.199504556 0.3425613646
## [49,] -1.293985797 -0.0004253878
## [50,] 0.473957215 -0.5128324222
## [51,] -0.156516787 -0.2706441690
## [52,] -0.541329295 -0.4305252373
## [53,] -0.881569689 -0.7779965334
## [54,] -0.251067307 -0.2654246353
## [55,] -0.735518713 -0.0894388216
## [56,] -0.768541512 -0.4536437835
## [57,] -0.971004194 -0.5111920070
## [58,] -0.387397975 0.1625615572
## [59,] -0.223573062 -0.1272030084
## [60,] -0.464352472 -0.2751566939
## [61,] -0.274573557 -0.2658123652
## [62,] -0.299860440 -0.0005001317
## [63,] -0.361742341 0.2139495832
## [64,] -0.335682045 0.4407726897
## [65,] -0.489790430 0.3054291932
## [66,] -1.704719872 -0.8058805584
## [67,] 0.246937314 0.0637453732
## [68,] -0.477084004 -0.2891884349
## [69,] 0.136868864 0.8387374081
## [70,] 0.658974293 0.4084289540
## [71,] 0.409921136 0.5107326592
## [72,] 0.598454181 0.4005520978
## [73,] 0.631886719 1.5307911187
## [74,] 0.740980728 0.9980552319
## [75,] -0.048166456 0.4899767214
## [76,] 0.310499428 0.3492806718
## [77,] -0.331720331 1.4724002575
## [78,] -0.861051459 -0.3386122066
## [79,] -0.521260301 -0.6448758563
## [80,] -1.061183191 -0.7987106395
## [81,] -0.205335471 0.4189814318
## [82,] -0.690766081 0.5967887160
## [83,] 0.301288216 -0.5304153764
## [84,] -0.644990235 -0.6471620442
## [85,] 0.367899435 0.3914733357
## [86,] 0.399992284 0.7640360476
## [87,] -1.128988238 0.5650386073
## [88,] -0.763399716 -0.5722490407
## [89,] -0.682777863 -0.0897901166
## [90,] -0.869596817 -0.7970330051
## [91,] -0.809074466 0.5612993289
## [92,] 0.256319113 0.6955036416
## [93,] -0.321615798 0.1181572875
## [94,] 0.084572631 -0.7379788280
## [95,] -0.178295596 -0.4180191378
## [96,] -0.487749630 -0.2569050303
## [97,] -1.158732900 -0.1972115826
## [98,] -0.239996388 0.2460137873
## [99,] 0.189261180 -0.4284545286
## [100,] -1.016483452 0.1633479825
## [101,] -0.306469172 -1.1306654772
## [102,] -0.359135538 -0.8740533105
## [103,] -0.860822207 1.0567536285
## [104,] -0.435890385 -0.5522188055
## [105,] 0.055269832 -0.1495077330
## [106,] 0.535704466 0.7127630521
## [107,] -1.058704656 -0.8129761421
## [108,] 0.210247858 0.8698785260
## [109,] -0.038642016 0.0196176411
## [110,] -0.059725383 -1.4236634055
## [111,] 0.089281361 0.8278503530
## [112,] 0.382802012 -0.0444196855
## [113,] -0.431221863 0.0061656526
## [114,] -1.168240047 -0.9041111361
## [115,] -1.062385516 -0.4993016766
## [116,] -0.725325172 -0.3700249716
## [117,] 0.581942679 -1.5494297073
## [118,] 1.490987969 0.0740346249
## [119,] -0.059153768 0.7250033437
## [120,] -0.055430164 0.4205130022
## [121,] 0.274462621 -1.8683102274
## [122,] -0.208194065 0.3935732747
## [123,] -0.698583661 0.2671479071
## [124,] -0.698661169 -0.0434721448
## [125,] -0.606230193 -0.1028593442
## [126,] -0.423367240 -0.3584987275
## [127,] -0.577623578 -0.2290724729
## [128,] -0.752647516 0.7860468935
## [129,] -0.810179406 -0.0058850116
## [130,] -0.857810187 -0.0581711075
## [131,] -0.844028222 -0.2386102424
## [132,] -1.168786366 -0.7662664091
## [133,] -0.696273207 -0.4733346584
## [134,] -0.917008385 -0.2181001366
## [135,] -1.239598078 -0.4253775478
## [136,] -1.318460942 -0.0608280067
## [137,] -0.858249997 -1.9064958007
## [138,] -1.302780338 -0.7430693984
## [139,] -0.542325272 -0.6776472690
## [140,] 0.500237422 -0.5346351724
## [141,] -0.223992608 0.3755823359
## [142,] -0.292732921 -0.3844388998
## [143,] -0.356381903 -0.3127835361
## [144,] -1.029782605 0.3907972339
## [145,] -0.748475876 -1.7157298528
## [146,] -1.448205854 -1.0579562265
## [147,] -1.212704151 -0.4330174387
## [148,] -0.930790479 -0.3290920863
## [149,] -0.408326423 -0.2163928611
## [150,] -0.809223499 -0.6405144044
## [151,] -0.805415090 0.0906541123
## [152,] -0.418092585 -0.5300561961
## [153,] -0.593657603 -0.8227560203
## [154,] 4.089966685 -0.7432376656
## [155,] -0.929953867 -0.3231587280
## [156,] -0.435928650 -0.6517716569
## [157,] 1.110605273 0.1159932061
## [158,] 0.705694188 1.0211624302
## [159,] -0.418801896 -0.0191469722
## [160,] 0.152209205 -0.0552841324
## [161,] -0.109864877 -1.5126923864
## [162,] -0.642484569 -1.1098576294
## [163,] 0.664580419 0.3001196668
## [164,] 0.120496468 0.4212351267
## [165,] 0.903121967 1.3191382467
## [166,] 0.490976428 0.8893490446
## [167,] -0.372892008 0.2126861164
## [168,] 0.081184668 -0.1068578056
## [169,] -0.228451598 -0.4967530600
## [170,] 0.247070558 -0.4460225159
## [171,] 0.373692041 -0.1760725365
## [172,] 0.532672825 0.1105436249
## [173,] -0.415736777 0.2616285143
## [174,] -0.947295129 -1.1900415353
## [175,] -0.628324267 0.2082155425
## [176,] 0.318709936 -0.3396994880
## [177,] 1.108783594 -0.1330556703
## [178,] -0.283039335 -0.3392426173
## [179,] -0.302234720 -0.0279126988
## [180,] 0.163576360 -0.3367367003
## [181,] 0.071907714 1.1632387779
## [182,] -0.602676116 0.3945805659
## [183,] 0.710705753 -0.0731050586
## [184,] 0.931539876 0.3266714857
## [185,] 1.440551058 0.4637668729
## [186,] 0.490583736 -0.6777713968
## [187,] 0.968031329 0.1738170188
## [188,] -0.084839671 0.2285619942
## [189,] 0.167943709 -0.4313264098
## [190,] -0.084245945 -0.5290966045
## [191,] 0.197132682 0.6249443893
## [192,] 0.763910637 0.2592653936
## [193,] -0.837182802 -0.1044299645
## [194,] 0.176984300 -0.6029868675
## [195,] -0.477027353 0.2703940748
## [196,] -0.704371527 -0.4797975687
## [197,] -2.273241276 -1.4824217526
## [198,] 1.148144464 0.2208401278
## [199,] 0.540498742 0.0562029469
## [200,] 0.262401886 0.4983674669
## [201,] -1.608641506 -0.3776177468
## [202,] 0.624463662 0.2851166983
## [203,] -0.380799595 -0.4204464320
## [204,] -0.633207943 -0.7148925620
## [205,] 0.027605725 -0.4923897696
## [206,] -0.360462186 -1.0128207199
## [207,] -0.800428730 -0.5683011124
## [208,] -0.929536660 -0.2866209632
## [209,] 1.960343828 0.2571345531
## [210,] 0.056305588 0.1891526594
## [211,] -0.149627262 0.5686295510
## [212,] 0.193675689 -0.0363798595
## [213,] -0.285857553 0.4391161334
## [214,] 0.254482351 -0.1801519630
## [215,] 6.322377664 -0.1792464220
## [216,] -0.391370455 0.2647782753
## [217,] -0.080428684 -0.0336068467
## [218,] -0.061792078 -1.0375516919
## [219,] 0.385103317 0.3500481832
## [220,] 0.483306876 -0.0268925691
## [221,] -0.589328589 -0.2528410282
## [222,] -1.230685154 -0.4888637740
## [223,] 1.198281563 -0.6151156723
## [224,] 0.370758130 0.0566635689
## [225,] 0.003837204 0.8795114023
## [226,] 1.432288368 0.6824719241
## [227,] -0.206623533 0.0035436244
## [228,] -0.020992043 -0.3954225109
## [229,] 0.046058860 0.0991558912
## [230,] 0.182654038 0.0127503142
## [231,] -0.810625060 -1.2518939378
## [232,] 5.873266335 0.4998294485
## [233,] 0.449157928 -0.7269458954
## [234,] 0.349695647 0.4245763482
## [235,] 0.578374515 1.0572493205
## [236,] 0.131492188 -0.0696340759
## [237,] 1.339931245 0.8698836697
## [238,] 0.483653489 0.7883033439
## [239,] 0.913056147 0.5630056422
## [240,] -3.688335623 13.6600254604
## [241,] -0.499136463 0.0036900841
## [242,] 1.727246461 0.1508922064
## [243,] 0.662367524 0.1266156180
## [244,] 0.173555000 -1.0507018022
## [245,] 1.081318036 0.0545426981
## [246,] 0.214948267 0.3654606131
## [247,] 1.891821433 1.1673121730
## [248,] 0.153376745 -0.6317348191
## [249,] 1.338686631 0.2021545229
## [250,] 0.683447976 0.2318899255
## [251,] -1.145451480 -0.3333854178
## [252,] 0.404118320 0.6578342269
## [253,] 1.147618677 0.3982604997
## [254,] 1.514875428 -0.3727548942
## [255,] -0.552456220 -0.6325167584
## [256,] 0.536825812 0.7532937116
## [257,] 0.021038641 0.4606953102
## [258,] 3.138292872 -0.5706138711
## [259,] 0.686863205 0.9039989029
## [260,] 0.686560112 0.4601510414
## [261,] -0.116002497 0.1204763616
## [262,] 0.140960064 0.5950361379
## [263,] 0.335114533 0.5939569761
## [264,] 0.564735350 -0.0431035319
## [265,] -0.110955230 0.1471643655
## [266,] 0.970448395 -0.0430907847
## [267,] 0.052867002 0.4022825677
## [268,] 1.333809692 0.5383941140
## [269,] 2.291387297 -0.4403122769
## [270,] 0.470168965 1.0149186776
## [271,] 3.785612647 0.5902259631
## [272,] 0.395392069 0.6276341463
## [273,] 3.880036424 -0.5457431711
## [274,] 0.887809085 0.0304051119
## [275,] 1.370807648 1.0471881228
## [276,] 0.732666362 -0.1965819686
## [277,] 0.461136088 0.4445271895
## [278,] 1.701041973 -0.1903585600
## [279,] 2.062524466 -0.1122780978
## [280,] 0.936807454 0.7807630388
## [281,] 1.350708515 -0.0218642681
## [282,] -0.836849715 -1.6773189829
## [283,] 1.429129472 -2.6013967133
## [284,] 0.987123238 1.1571549461
## [285,] 0.726525230 0.7357404147
## [286,] 1.831278429 0.1122841298
## [287,] 0.539511476 0.6816930406
## [288,] 1.236590339 0.2764017622
## [289,] -0.150442661 -0.8927716116
## [290,] 0.206524679 0.5435466567
## [291,] -0.046135969 0.4065189250
## [292,] -0.688086978 -0.6180015280
## [293,] -0.468908743 -0.0567330459
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## [299,] 0.833491210 0.5667412930
## [300,] -0.069877479 -0.4634537765
## [301,] -0.058253443 -0.1301357137
## [302,] 0.590319003 0.4407549468
## [303,] -0.842038062 -0.6697954081
## [304,] 0.224583844 -0.4226172110
## [305,] -0.030622491 1.1054665539
## [306,] 0.799837370 0.4214899339
## [307,] 0.255893473 0.2492555946
## [308,] 0.270600680 0.6945314996
## [309,] 0.609651682 0.5653995155
## [310,] -0.040393953 1.3037641856
## [311,] 0.228758871 -0.1163758882
## [312,] -0.205255085 -0.1572179483
## [313,] 0.085999435 -0.5813744962
## [314,] -0.170529665 0.3894844128
## [315,] 1.476551950 0.5871617294
## [316,] -0.866025927 -0.0590653957
## [317,] 0.203990851 0.2379950850
## [318,] 0.061270324 -1.1924258796
## [319,] -0.027591800 2.5806805638