Latent Profile Analysis
Melissa-Ann Lagunas
2023-03-08
#import data
library(readr)
data <- read_csv("~/Desktop/Lab/FirstGen Professional/FGP Exploratory Study/FGP Exploratory Study Analyses/data.csv")## New names:
## Rows: 211 Columns: 30
## ── Column specification
## ──────────────────────────────────────────────────────── Delimiter: "," chr
## (7): recruitment, year, occupation, duration, Q19, Q22, Q23 dbl (23): ...1, ID,
## age, gender, sexuality, born, ethnicity, income, fam_inc...
## ℹ Use `spec()` to retrieve the full column specification for this data. ℹ
## Specify the column types or set `show_col_types = FALSE` to quiet this message.
## • `` -> `...1`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, unionfgp_data <- data %>% filter(fgp == '1')
d <- data.frame(fgp_data$sap_stand, fgp_data$sap_dis, fgp_data$anxiety, fgp_data$depression, fgp_data$wswb, fgp_data$wellbeing)
d <- rename(d, standards = fgp_data.sap_stand, discrepancy = fgp_data.sap_dis, anxiety = fgp_data.anxiety, depression = fgp_data.depression, swfw = fgp_data.wswb, wellbeing = fgp_data.wellbeing)
write.csv(d, file = "fgp_lpa_data.csv", row.names = FALSE)Using kmeans
#make a dataframe of just standards and discrepancies
cluster_data <- data.frame(d$standards, d$discrepancy)
cluster_data <- rename(cluster_data,standards = d.standards, discrepancy = d.discrepancy )
# remove missing data
cluster_data <- na.omit(cluster_data)
# scale the data
d_scaled <- scale(cluster_data)
d_scaled## standards discrepancy
## 1 1.21645598 1.46427775
## 2 -0.49223094 -0.46681334
## 3 -0.73632907 -1.43235889
## 4 -1.46862347 -0.94958612
## 5 0.72825971 0.74011859
## 6 -0.98042720 -0.70819973
## 7 -1.22452534 -1.43235889
## 8 -0.98042720 -0.46681334
## 9 -0.24813281 -0.22542696
## 10 1.21645598 1.22289137
## 11 0.97235784 0.98150498
## 12 -0.24813281 -0.46681334
## 13 0.24006345 0.25734582
## 14 -0.73632907 -0.70819973
## 15 0.97235784 0.98150498
## 16 -0.73632907 -0.70819973
## 17 1.21645598 1.22289137
## 18 -0.24813281 -0.70819973
## 19 -0.00403468 0.01595943
## 20 -0.73632907 -0.22542696
## 21 1.21645598 1.22289137
## 22 -1.22452534 -1.43235889
## 23 -0.24813281 -0.22542696
## 24 -0.24813281 -0.46681334
## 25 0.48416158 0.25734582
## 26 -0.00403468 -0.22542696
## 27 1.70465224 1.70566414
## 28 1.70465224 1.70566414
## 29 0.97235784 0.49873220
## 30 1.46055411 1.22289137
## 31 0.97235784 0.74011859
## 32 -0.24813281 -0.22542696
## 33 0.72825971 0.74011859
## 34 1.46055411 0.98150498
## 35 1.46055411 1.70566414
## 36 -0.98042720 -0.70819973
## 37 -0.00403468 0.01595943
## 38 0.72825971 0.74011859
## 39 0.24006345 0.25734582
## 40 -1.71272160 -1.67374528
## 41 -1.22452534 -1.19097251
## 42 0.48416158 0.74011859
## 43 -0.73632907 -0.70819973
## 44 -0.49223094 -0.46681334
## 45 -0.98042720 -0.70819973
## 46 0.72825971 0.74011859
## 47 -0.49223094 -0.46681334
## 48 -0.73632907 -0.46681334
## 49 1.21645598 0.49873220
## 50 -1.46862347 -1.67374528
## 51 0.48416158 0.49873220
## 52 0.72825971 0.74011859
## 53 -1.22452534 -1.19097251
## 54 -0.73632907 -0.70819973
## 55 1.70465224 1.70566414
## 56 0.48416158 0.49873220
## 57 -1.71272160 -1.67374528
## 58 -0.24813281 0.01595943
## 59 -0.49223094 -1.19097251
## 60 0.24006345 -0.46681334
## 61 -0.73632907 -0.70819973
## 62 1.70465224 1.70566414
## 63 0.48416158 0.25734582
## 64 -1.22452534 -1.43235889
## 65 1.46055411 1.70566414
## 66 0.72825971 1.22289137
## 67 1.46055411 0.98150498
## 68 1.46055411 1.70566414
## 69 0.97235784 1.22289137
## 70 0.48416158 0.49873220
## 71 0.72825971 0.74011859
## 72 1.21645598 0.74011859
## 73 0.48416158 0.25734582
## 74 -0.73632907 -0.94958612
## 75 0.97235784 1.22289137
## 76 0.48416158 0.49873220
## 77 -0.73632907 -0.22542696
## 78 0.97235784 0.74011859
## 79 0.24006345 0.25734582
## 80 -0.73632907 -0.70819973
## 81 -1.71272160 -1.91513167
## 82 -0.49223094 0.25734582
## 83 0.72825971 0.74011859
## 84 -0.24813281 -0.22542696
## 85 0.24006345 0.25734582
## 86 -0.73632907 -0.70819973
## 87 -1.46862347 -1.19097251
## 88 0.72825971 0.74011859
## 89 1.70465224 1.70566414
## 90 0.72825971 0.49873220
## 91 -1.46862347 -1.43235889
## 92 0.48416158 1.70566414
## 93 0.97235784 0.98150498
## 94 -0.98042720 -0.94958612
## 95 0.97235784 1.22289137
## 96 -0.49223094 -0.46681334
## 97 -0.49223094 -0.22542696
## 98 0.72825971 0.74011859
## 99 -0.24813281 -0.22542696
## 100 0.24006345 0.25734582
## 101 1.21645598 0.74011859
## 102 -1.71272160 -1.91513167
## 103 -0.49223094 -0.46681334
## 104 0.24006345 0.25734582
## 105 -0.73632907 -0.70819973
## 106 1.70465224 1.70566414
## 107 -0.73632907 -0.70819973
## 108 0.72825971 0.25734582
## 109 -0.73632907 -0.70819973
## 110 -1.22452534 -1.67374528
## 111 -1.22452534 -1.19097251
## 112 -1.46862347 -1.43235889
## 113 -1.22452534 -1.19097251
## 114 -0.73632907 -0.94958612
## 115 1.46055411 1.46427775
## 116 -0.24813281 -0.94958612
## 117 -1.22452534 -1.19097251
## 118 -0.00403468 0.01595943
## 119 -2.20091786 -2.15651805
## 120 -0.24813281 -0.22542696
## 121 -1.71272160 -0.22542696
## attr(,"scaled:center")
## standards discrepancy
## 21.01653 20.93388
## attr(,"scaled:scale")
## standards discrepancy
## 4.096713 4.142736library(factoextra)## Loading required package: ggplot2## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa#calculate distance metrics between oberservations
distance <- dist(d_scaled)
distance## 1 2 3 4 5 6 7
## 2 2.5785119
## 3 3.4934043 0.9959227
## 4 3.6105942 1.0892254 0.8771115
## 5 0.8733511 1.7164738 2.6200532 2.7715335
## 6 3.0896528 0.5446127 0.7641926 0.5446127 2.2399190
## 7 3.7879933 1.2118306 0.4881963 0.5409745 2.9211347 0.7641926
## 8 2.9249630 0.4881963 0.9959227 0.6865895 2.0919598 0.2413864 0.9959227
## 9 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 10 0.2413864 2.4030633 3.2960163 3.4538833 0.6865895 2.9249630 3.6067636
## 11 0.5409745 2.0597685 2.9574228 3.1124753 0.3432948 2.5823384 3.2638987
## 12 2.4236611 0.2440981 1.0819491 1.3125041 1.5524262 0.7710528 1.3731790
## 13 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 14 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 15 0.5409745 2.0597685 2.9574228 3.1124753 0.3432948 2.5823384 3.2638987
## 16 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 17 0.2413864 2.4030633 3.2960163 3.4538833 0.6865895 2.9249630 3.6067636
## 18 2.6200532 0.3432948 0.8733511 1.2441322 1.7467021 0.7322944 1.2156269
## 19 1.8939967 0.6865895 1.6229236 1.7542231 1.0298843 1.2156269 1.8939967
## 20 2.5823384 0.3432948 1.2069319 1.0298843 1.7542231 0.5409745 1.3019294
## 21 0.2413864 2.4030633 3.2960163 3.4538833 0.6865895 2.9249630 3.6067636
## 22 3.7879933 1.2118306 0.4881963 0.5409745 2.9211347 0.7641926 0.0000000
## 23 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 24 2.4236611 0.2440981 1.0819491 1.3125041 1.5524262 0.7710528 1.3731790
## 25 1.4117152 1.2156269 2.0843943 2.2956598 0.5409745 1.7542231 2.4030633
## 26 2.0843943 0.5446127 1.4117152 1.6338381 1.2118306 1.0892254 1.7164738
## 27 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 28 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 29 0.9959227 1.7542231 2.5785119 2.8383121 0.3432948 2.2956598 2.9249630
## 30 0.3432948 2.5823384 3.4462515 3.6468808 0.8771115 3.1124753 3.7762423
## 31 0.7641926 1.8978159 2.7639228 2.9687526 0.2440981 2.4312539 3.0896528
## 32 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 33 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 34 0.5409745 2.4312539 3.2638987 3.5084461 0.7710528 2.9687526 3.6105942
## 35 0.3432948 2.9211347 3.8305984 3.9535345 1.2118306 3.4329475 4.1299928
## 36 3.0896528 0.5446127 0.7641926 0.5446127 2.2399190 0.0000000 0.7641926
## 37 1.8939967 0.6865895 1.6229236 1.7542231 1.0298843 1.2156269 1.8939967
## 38 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 39 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 40 4.2926996 1.7164738 1.0057881 0.7641926 3.4329475 1.2118306 0.5446127
## 41 3.6067636 1.0298843 0.5446127 0.3432948 2.7463580 0.5409745 0.2413864
## 42 1.0298843 1.5524262 2.4918378 2.5823384 0.2440981 2.0597685 2.7639228
## 43 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 44 2.5785119 0.0000000 0.9959227 1.0892254 1.7164738 0.5446127 1.2118306
## 45 3.0896528 0.5446127 0.7641926 0.5446127 2.2399190 0.0000000 0.7641926
## 46 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 47 2.5785119 0.0000000 0.9959227 1.0892254 1.7164738 0.5446127 1.2118306
## 48 2.7463580 0.2440981 0.9655455 0.8771115 1.8978159 0.3432948 1.0819491
## 49 0.9655455 1.9626230 2.7463580 3.0507831 0.5446127 2.5065874 3.1124753
## 50 4.1299928 1.5524262 0.7710528 0.7241592 3.2638987 1.0819491 0.3432948
## 51 1.2118306 1.3731790 2.2844497 2.4312539 0.3432948 1.8978159 2.5785119
## 52 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 53 3.6067636 1.0298843 0.5446127 0.3432948 2.7463580 0.5409745 0.2413864
## 54 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 55 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 56 1.2118306 1.3731790 2.2844497 2.4312539 0.3432948 1.8978159 2.5785119
## 57 4.2926996 1.7164738 1.0057881 0.7641926 3.4329475 1.2118306 0.5446127
## 58 2.0597685 0.5409745 1.5283853 1.5562377 1.2156269 1.0298843 1.7467021
## 59 3.1575251 0.7241592 0.3432948 1.0057881 2.2844497 0.6865895 0.7710528
## 60 2.1638981 0.7322944 1.3731790 1.7755789 1.3019294 1.2441322 1.7542231
## 61 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 62 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 63 1.4117152 1.2156269 2.0843943 2.2956598 0.5409745 1.7542231 2.4030633
## 64 3.7879933 1.2118306 0.4881963 0.5409745 2.9211347 0.7641926 0.0000000
## 65 0.3432948 2.9211347 3.8305984 3.9535345 1.2118306 3.4329475 4.1299928
## 66 0.5446127 2.0843943 3.0323875 3.0896528 0.4827728 2.5785119 3.2960163
## 67 0.5409745 2.4312539 3.2638987 3.5084461 0.7710528 2.9687526 3.6105942
## 68 0.3432948 2.9211347 3.8305984 3.9535345 1.2118306 3.4329475 4.1299928
## 69 0.3432948 2.2360953 3.1575251 3.2677283 0.5409745 2.7463580 3.4462515
## 70 1.2118306 1.3731790 2.2844497 2.4312539 0.3432948 1.8978159 2.5785119
## 71 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 72 0.7241592 2.0919598 2.9211347 3.1724996 0.4881963 2.6313346 3.2677283
## 73 1.4117152 1.2156269 2.0843943 2.2956598 0.5409745 1.7542231 2.4030633
## 74 3.1048524 0.5409745 0.4827728 0.7322944 2.2360953 0.3432948 0.6865895
## 75 0.3432948 2.2360953 3.1575251 3.2677283 0.5409745 2.7463580 3.4462515
## 76 1.2118306 1.3731790 2.2844497 2.4312539 0.3432948 1.8978159 2.5785119
## 77 2.5823384 0.3432948 1.2069319 1.0298843 1.7542231 0.5409745 1.3019294
## 78 0.7641926 1.8978159 2.7639228 2.9687526 0.2440981 2.4312539 3.0896528
## 79 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 80 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 81 4.4721907 1.8939967 1.0892254 0.9959227 3.6067636 1.4117152 0.6865895
## 82 2.0919598 0.7241592 1.7072451 1.5524262 1.3125041 1.0819491 1.8415638
## 83 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 84 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 85 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 86 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 87 3.7762423 1.2156269 0.7710528 0.2413864 2.9249630 0.6865895 0.3432948
## 88 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 89 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 90 1.0819491 1.5562377 2.4236611 2.6313346 0.2413864 2.0919598 2.7463580
## 91 3.9497032 1.3731790 0.7322944 0.4827728 3.0896528 0.8733511 0.2440981
## 92 0.7710528 2.3818062 3.3670144 3.2960163 0.9959227 2.8234304 3.5730658
## 93 0.5409745 2.0597685 2.9574228 3.1124753 0.3432948 2.5823384 3.2638987
## 94 3.2638987 0.6865895 0.5409745 0.4881963 2.4030633 0.2413864 0.5409745
## 95 0.3432948 2.2360953 3.1575251 3.2677283 0.5409745 2.7463580 3.4462515
## 96 2.5785119 0.0000000 0.9959227 1.0892254 1.7164738 0.5446127 1.2118306
## 97 2.4030633 0.2413864 1.2313686 1.2156269 1.5562377 0.6865895 1.4117152
## 98 0.8733511 1.7164738 2.6200532 2.7715335 0.0000000 2.2399190 2.9211347
## 99 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 100 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 101 0.7241592 2.0919598 2.9211347 3.1724996 0.4881963 2.6313346 3.2677283
## 102 4.4721907 1.8939967 1.0892254 0.9959227 3.6067636 1.4117152 0.6865895
## 103 2.5785119 0.0000000 0.9959227 1.0892254 1.7164738 0.5446127 1.2118306
## 104 1.5524262 1.0298843 1.9515236 2.0919598 0.6865895 1.5562377 2.2360953
## 105 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 106 0.5446127 3.0896528 3.9756230 4.1376361 1.3731790 3.6105942 4.2926996
## 107 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 108 1.3019294 1.4191561 2.2360953 2.5065874 0.4827728 1.9626230 2.5823384
## 109 2.9211347 0.3432948 0.7241592 0.7710528 2.0597685 0.2440981 0.8733511
## 110 3.9756230 1.4117152 0.5446127 0.7641926 3.1048524 0.9959227 0.2413864
## 111 3.6067636 1.0298843 0.5446127 0.3432948 2.7463580 0.5409745 0.2413864
## 112 3.9497032 1.3731790 0.7322944 0.4827728 3.0896528 0.8733511 0.2440981
## 113 3.6067636 1.0298843 0.5446127 0.3432948 2.7463580 0.5409745 0.2413864
## 114 3.1048524 0.5409745 0.4827728 0.7322944 2.2360953 0.3432948 0.6865895
## 115 0.2440981 2.7463580 3.6354917 3.7956317 1.0298843 3.2677283 3.9497032
## 116 2.8234304 0.5409745 0.6865895 1.2204907 1.9515236 0.7710528 1.0892254
## 117 3.6067636 1.0298843 0.5446127 0.3432948 2.7463580 0.5409745 0.2413864
## 118 1.8939967 0.6865895 1.6229236 1.7542231 1.0298843 1.2156269 1.8939967
## 119 4.9788157 2.4030633 1.6338381 1.4117152 4.1195370 1.8939967 1.2156269
## 120 2.2360953 0.3432948 1.3019294 1.4191561 1.3731790 0.8771115 1.5524262
## 121 3.3815948 1.2441322 1.5524262 0.7641926 2.6250082 0.8771115 1.3019294
## 8 9 10 11 12 13 14
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9 0.7710528
## 10 2.7715335 2.0597685
## 11 2.4312539 1.7164738 0.3432948
## 12 0.7322944 0.2413864 2.2360953 1.8939967
## 13 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511
## 14 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790
## 15 2.4312539 1.7164738 0.3432948 0.0000000 1.8939967 1.0298843 2.4030633
## 16 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 17 2.7715335 2.0597685 0.0000000 0.3432948 2.2360953 1.3731790 2.7463580
## 18 0.7710528 0.4827728 2.4236611 2.0843943 0.2413864 1.0819491 0.4881963
## 19 1.0892254 0.3432948 1.7164738 1.3731790 0.5409745 0.3432948 1.0298843
## 20 0.3432948 0.4881963 2.4312539 2.0919598 0.5446127 1.0892254 0.4827728
## 21 2.7715335 2.0597685 0.0000000 0.3432948 2.2360953 1.3731790 2.7463580
## 22 0.9959227 1.5524262 3.6067636 3.2638987 1.3731790 2.2360953 0.8733511
## 23 0.7710528 0.0000000 2.0597685 1.7164738 0.2413864 0.6865895 0.6865895
## 24 0.7322944 0.2413864 2.2360953 1.8939967 0.0000000 0.8733511 0.5446127
## 25 1.6338381 0.8771115 1.2118306 0.8733511 1.0298843 0.2440981 1.5562377
## 26 1.0057881 0.2440981 1.8939967 1.5524262 0.3432948 0.5409745 0.8771115
## 27 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 28 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 29 2.1784507 1.4191561 0.7641926 0.4827728 1.5562377 0.7710528 2.0919598
## 30 2.9687526 2.2399190 0.2440981 0.5446127 2.4030633 1.5562377 2.9249630
## 31 2.2956598 1.5562377 0.5409745 0.2413864 1.7164738 0.8771115 2.2399190
## 32 0.7710528 0.0000000 2.0597685 1.7164738 0.2413864 0.6865895 0.6865895
## 33 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 34 2.8383121 2.0919598 0.3432948 0.4881963 2.2399190 1.4191561 2.7715335
## 35 3.2677283 2.5785119 0.5409745 0.8733511 2.7639228 1.8939967 3.2638987
## 36 0.2413864 0.8771115 2.9249630 2.5823384 0.7710528 1.5562377 0.2440981
## 37 1.0892254 0.3432948 1.7164738 1.3731790 0.5409745 0.3432948 1.0298843
## 38 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 39 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511 0.0000000 1.3731790
## 40 1.4117152 2.0597685 4.1195370 3.7762423 1.8978159 2.7463580 1.3731790
## 41 0.7641926 1.3731790 3.4329475 3.0896528 1.2156269 2.0597685 0.6865895
## 42 1.8978159 1.2118306 0.8771115 0.5446127 1.4117152 0.5409745 1.8939967
## 43 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 44 0.4881963 0.3432948 2.4030633 2.0597685 0.2440981 1.0298843 0.3432948
## 45 0.2413864 0.8771115 2.9249630 2.5823384 0.7710528 1.5562377 0.2440981
## 46 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 47 0.4881963 0.3432948 2.4030633 2.0597685 0.2440981 1.0298843 0.3432948
## 48 0.2440981 0.5446127 2.5823384 2.2399190 0.4881963 1.2156269 0.2413864
## 49 2.3997029 1.6338381 0.7241592 0.5409745 1.7542231 1.0057881 2.2956598
## 50 1.3019294 1.8939967 3.9497032 3.6067636 1.7164738 2.5785119 1.2118306
## 51 1.7542231 1.0298843 1.0298843 0.6865895 1.2118306 0.3432948 1.7164738
## 52 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 53 0.7641926 1.3731790 3.4329475 3.0896528 1.2156269 2.0597685 0.6865895
## 54 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 55 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 56 1.7542231 1.0298843 1.0298843 0.6865895 1.2118306 0.3432948 1.7164738
## 57 1.4117152 2.0597685 4.1195370 3.7762423 1.8978159 2.7463580 1.3731790
## 58 0.8771115 0.2413864 1.8978159 1.5562377 0.4827728 0.5446127 0.8733511
## 59 0.8733511 0.9959227 2.9574228 2.6200532 0.7641926 1.6229236 0.5409745
## 60 1.2204907 0.5446127 1.9515236 1.6229236 0.4881963 0.7241592 1.0057881
## 61 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 62 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 63 1.6338381 0.8771115 1.2118306 0.8733511 1.0298843 0.2440981 1.5562377
## 64 0.9959227 1.5524262 3.6067636 3.2638987 1.3731790 2.2360953 0.8733511
## 65 3.2677283 2.5785119 0.5409745 0.8733511 2.7639228 1.8939967 3.2638987
## 66 2.4030633 1.7467021 0.4881963 0.3432948 1.9515236 1.0819491 2.4236611
## 67 2.8383121 2.0919598 0.3432948 0.4881963 2.2399190 1.4191561 2.7715335
## 68 3.2677283 2.5785119 0.5409745 0.8733511 2.7639228 1.8939967 3.2638987
## 69 2.5823384 1.8939967 0.2440981 0.2413864 2.0843943 1.2118306 2.5785119
## 70 1.7542231 1.0298843 1.0298843 0.6865895 1.2118306 0.3432948 1.7164738
## 71 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 72 2.5065874 1.7542231 0.4827728 0.3432948 1.8978159 1.0892254 2.4312539
## 73 1.6338381 0.8771115 1.2118306 0.8733511 1.0298843 0.2440981 1.5562377
## 74 0.5409745 0.8733511 2.9211347 2.5785119 0.6865895 1.5524262 0.2413864
## 75 2.5823384 1.8939967 0.2440981 0.2413864 2.0843943 1.2118306 2.5785119
## 76 1.7542231 1.0298843 1.0298843 0.6865895 1.2118306 0.3432948 1.7164738
## 77 0.3432948 0.4881963 2.4312539 2.0919598 0.5446127 1.0892254 0.4827728
## 78 2.2956598 1.5562377 0.5409745 0.2413864 1.7164738 0.8771115 2.2399190
## 79 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511 0.0000000 1.3731790
## 80 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 81 1.6229236 2.2360953 4.2926996 3.9497032 2.0597685 2.9211347 1.5524262
## 82 0.8733511 0.5409745 1.9626230 1.6338381 0.7641926 0.7322944 0.9959227
## 83 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 84 0.7710528 0.0000000 2.0597685 1.7164738 0.2413864 0.6865895 0.6865895
## 85 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511 0.0000000 1.3731790
## 86 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 87 0.8733511 1.5562377 3.6105942 3.2677283 1.4191561 2.2399190 0.8771115
## 88 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 89 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 90 1.9626230 1.2156269 0.8733511 0.5409745 1.3731790 0.5446127 1.8978159
## 91 1.0819491 1.7164738 3.7762423 3.4329475 1.5562377 2.4030633 1.0298843
## 92 2.6200532 2.0652767 0.8771115 0.8733511 2.2925779 1.4687443 2.7048727
## 93 2.4312539 1.7164738 0.3432948 0.0000000 1.8939967 1.0298843 2.4030633
## 94 0.4827728 1.0298843 3.0896528 2.7463580 0.8771115 1.7164738 0.3432948
## 95 2.5823384 1.8939967 0.2440981 0.2413864 2.0843943 1.2118306 2.5785119
## 96 0.4881963 0.3432948 2.4030633 2.0597685 0.2440981 1.0298843 0.3432948
## 97 0.5446127 0.2440981 2.2399190 1.8978159 0.3432948 0.8771115 0.5409745
## 98 2.0919598 1.3731790 0.6865895 0.3432948 1.5524262 0.6865895 2.0597685
## 99 0.7710528 0.0000000 2.0597685 1.7164738 0.2413864 0.6865895 0.6865895
## 100 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511 0.0000000 1.3731790
## 101 2.5065874 1.7542231 0.4827728 0.3432948 1.8978159 1.0892254 2.4312539
## 102 1.6229236 2.2360953 4.2926996 3.9497032 2.0597685 2.9211347 1.5524262
## 103 0.4881963 0.3432948 2.4030633 2.0597685 0.2440981 1.0298843 0.3432948
## 104 1.4191561 0.6865895 1.3731790 1.0298843 0.8733511 0.0000000 1.3731790
## 105 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 106 3.4538833 2.7463580 0.6865895 1.0298843 2.9211347 2.0597685 3.4329475
## 107 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 108 1.8558064 1.0892254 1.0819491 0.7641926 1.2156269 0.4881963 1.7542231
## 109 0.3432948 0.6865895 2.7463580 2.4030633 0.5446127 1.3731790 0.0000000
## 110 1.2313686 1.7467021 3.7879933 3.4462515 1.5524262 2.4236611 1.0819491
## 111 0.7641926 1.3731790 3.4329475 3.0896528 1.2156269 2.0597685 0.6865895
## 112 1.0819491 1.7164738 3.7762423 3.4329475 1.5562377 2.4030633 1.0298843
## 113 0.7641926 1.3731790 3.4329475 3.0896528 1.2156269 2.0597685 0.6865895
## 114 0.5409745 0.8733511 2.9211347 2.5785119 0.6865895 1.5524262 0.2413864
## 115 3.1124753 2.4030633 0.3432948 0.6865895 2.5785119 1.7164738 3.0896528
## 116 0.8771115 0.7241592 2.6200532 2.2844497 0.4827728 1.3019294 0.5446127
## 117 0.7641926 1.3731790 3.4329475 3.0896528 1.2156269 2.0597685 0.6865895
## 118 1.0892254 0.3432948 1.7164738 1.3731790 0.5409745 0.3432948 1.0298843
## 119 2.0843943 2.7463580 4.8061265 4.4628318 2.5823384 3.4329475 2.0597685
## 120 0.7710528 0.0000000 2.0597685 1.7164738 0.2413864 0.6865895 0.6865895
## 121 0.7710528 1.4645888 3.2676761 2.9438642 1.4843476 2.0115762 1.0892254
## 15 16 17 18 19 20 21
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16 2.4030633
## 17 0.3432948 2.7463580
## 18 2.0843943 0.4881963 2.4236611
## 19 1.3731790 1.0298843 1.7164738 0.7641926
## 20 2.0919598 0.4827728 2.4312539 0.6865895 0.7710528
## 21 0.3432948 2.7463580 0.0000000 2.4236611 1.7164738 2.4312539
## 22 3.2638987 0.8733511 3.6067636 1.2156269 1.8939967 1.3019294 3.6067636
## 23 1.7164738 0.6865895 2.0597685 0.4827728 0.3432948 0.4881963 2.0597685
## 24 1.8939967 0.5446127 2.2360953 0.2413864 0.5409745 0.5446127 2.2360953
## 25 0.8733511 1.5562377 1.2118306 1.2118306 0.5446127 1.3125041 1.2118306
## 26 1.5524262 0.8771115 1.8939967 0.5409745 0.2413864 0.7322944 1.8939967
## 27 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 28 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 29 0.4827728 2.0919598 0.7641926 1.7164738 1.0892254 1.8558064 0.7641926
## 30 0.5446127 2.9249630 0.2440981 2.5785119 1.8978159 2.6313346 0.2440981
## 31 0.2413864 2.2399190 0.5409745 1.8939967 1.2156269 1.9626230 0.5409745
## 32 1.7164738 0.6865895 2.0597685 0.4827728 0.3432948 0.4881963 2.0597685
## 33 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 34 0.4881963 2.7715335 0.3432948 2.4030633 1.7542231 2.5065874 0.3432948
## 35 0.8733511 3.2638987 0.5409745 2.9574228 2.2360953 2.9249630 0.5409745
## 36 2.5823384 0.2440981 2.9249630 0.7322944 1.2156269 0.5409745 2.9249630
## 37 1.3731790 1.0298843 1.7164738 0.7641926 0.0000000 0.7710528 1.7164738
## 38 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 39 1.0298843 1.3731790 1.3731790 1.0819491 0.3432948 1.0892254 1.3731790
## 40 3.7762423 1.3731790 4.1195370 1.7542231 2.4030633 1.7467021 4.1195370
## 41 3.0896528 0.6865895 3.4329475 1.0892254 1.7164738 1.0819491 3.4329475
## 42 0.5446127 1.8939967 0.8771115 1.6229236 0.8733511 1.5562377 0.8771115
## 43 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 44 2.0597685 0.3432948 2.4030633 0.3432948 0.6865895 0.3432948 2.4030633
## 45 2.5823384 0.2440981 2.9249630 0.7322944 1.2156269 0.5409745 2.9249630
## 46 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 47 2.0597685 0.3432948 2.4030633 0.3432948 0.6865895 0.3432948 2.4030633
## 48 2.2399190 0.2413864 2.5823384 0.5446127 0.8771115 0.2413864 2.5823384
## 49 0.5409745 2.2956598 0.7241592 1.8978159 1.3125041 2.0827328 0.7241592
## 50 3.6067636 1.2118306 3.9497032 1.5562377 2.2360953 1.6229236 3.9497032
## 51 0.6865895 1.7164738 1.0298843 1.4117152 0.6865895 1.4191561 1.0298843
## 52 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 53 3.0896528 0.6865895 3.4329475 1.0892254 1.7164738 1.0819491 3.4329475
## 54 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 55 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 56 0.6865895 1.7164738 1.0298843 1.4117152 0.6865895 1.4191561 1.0298843
## 57 3.7762423 1.3731790 4.1195370 1.7542231 2.4030633 1.7467021 4.1195370
## 58 1.5562377 0.8733511 1.8978159 0.7241592 0.2440981 0.5446127 1.8978159
## 59 2.6200532 0.5409745 2.9574228 0.5409745 1.3019294 0.9959227 2.9574228
## 60 1.6229236 1.0057881 1.9515236 0.5446127 0.5409745 1.0057881 1.9515236
## 61 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 62 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 63 0.8733511 1.5562377 1.2118306 1.2118306 0.5446127 1.3125041 1.2118306
## 64 3.2638987 0.8733511 3.6067636 1.2156269 1.8939967 1.3019294 3.6067636
## 65 0.8733511 3.2638987 0.5409745 2.9574228 2.2360953 2.9249630 0.5409745
## 66 0.3432948 2.4236611 0.4881963 2.1638981 1.4117152 2.0597685 0.4881963
## 67 0.4881963 2.7715335 0.3432948 2.4030633 1.7542231 2.5065874 0.3432948
## 68 0.8733511 3.2638987 0.5409745 2.9574228 2.2360953 2.9249630 0.5409745
## 69 0.2413864 2.5785119 0.2440981 2.2844497 1.5524262 2.2399190 0.2440981
## 70 0.6865895 1.7164738 1.0298843 1.4117152 0.6865895 1.4191561 1.0298843
## 71 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 72 0.3432948 2.4312539 0.4827728 2.0597685 1.4191561 2.1784507 0.4827728
## 73 0.8733511 1.5562377 1.2118306 1.2118306 0.5446127 1.3125041 1.2118306
## 74 2.5785119 0.2413864 2.9211347 0.5446127 1.2118306 0.7241592 2.9211347
## 75 0.2413864 2.5785119 0.2440981 2.2844497 1.5524262 2.2399190 0.2440981
## 76 0.6865895 1.7164738 1.0298843 1.4117152 0.6865895 1.4191561 1.0298843
## 77 2.0919598 0.4827728 2.4312539 0.6865895 0.7710528 0.0000000 2.4312539
## 78 0.2413864 2.2399190 0.5409745 1.8939967 1.2156269 1.9626230 0.5409745
## 79 1.0298843 1.3731790 1.3731790 1.0819491 0.3432948 1.0892254 1.3731790
## 80 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 81 3.9497032 1.5524262 4.2926996 1.8978159 2.5785119 1.9515236 4.2926996
## 82 1.6338381 0.9959227 1.9626230 0.9959227 0.5446127 0.5409745 1.9626230
## 83 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 84 1.7164738 0.6865895 2.0597685 0.4827728 0.3432948 0.4881963 2.0597685
## 85 1.0298843 1.3731790 1.3731790 1.0819491 0.3432948 1.0892254 1.3731790
## 86 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 87 3.2677283 0.8771115 3.6105942 1.3125041 1.8978159 1.2118306 3.6105942
## 88 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 89 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 90 0.5409745 1.8978159 0.8733511 1.5524262 0.8771115 1.6338381 0.8733511
## 91 3.4329475 1.0298843 3.7762423 1.4191561 2.0597685 1.4117152 3.7762423
## 92 0.8733511 2.7048727 0.8771115 2.5224975 1.7588171 2.2844497 0.8771115
## 93 0.0000000 2.4030633 0.3432948 2.0843943 1.3731790 2.0919598 0.3432948
## 94 2.7463580 0.3432948 3.0896528 0.7710528 1.3731790 0.7641926 3.0896528
## 95 0.2413864 2.5785119 0.2440981 2.2844497 1.5524262 2.2399190 0.2440981
## 96 2.0597685 0.3432948 2.4030633 0.3432948 0.6865895 0.3432948 2.4030633
## 97 1.8978159 0.5409745 2.2399190 0.5409745 0.5446127 0.2440981 2.2399190
## 98 0.3432948 2.0597685 0.6865895 1.7467021 1.0298843 1.7542231 0.6865895
## 99 1.7164738 0.6865895 2.0597685 0.4827728 0.3432948 0.4881963 2.0597685
## 100 1.0298843 1.3731790 1.3731790 1.0819491 0.3432948 1.0892254 1.3731790
## 101 0.3432948 2.4312539 0.4827728 2.0597685 1.4191561 2.1784507 0.4827728
## 102 3.9497032 1.5524262 4.2926996 1.8978159 2.5785119 1.9515236 4.2926996
## 103 2.0597685 0.3432948 2.4030633 0.3432948 0.6865895 0.3432948 2.4030633
## 104 1.0298843 1.3731790 1.3731790 1.0819491 0.3432948 1.0892254 1.3731790
## 105 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 106 1.0298843 3.4329475 0.6865895 3.1048524 2.4030633 3.1124753 0.6865895
## 107 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 108 0.7641926 1.7542231 1.0819491 1.3731790 0.7710528 1.5421057 1.0819491
## 109 2.4030633 0.0000000 2.7463580 0.4881963 1.0298843 0.4827728 2.7463580
## 110 3.4462515 1.0819491 3.7879933 1.3731790 2.0843943 1.5283853 3.7879933
## 111 3.0896528 0.6865895 3.4329475 1.0892254 1.7164738 1.0819491 3.4329475
## 112 3.4329475 1.0298843 3.7762423 1.4191561 2.0597685 1.4117152 3.7762423
## 113 3.0896528 0.6865895 3.4329475 1.0892254 1.7164738 1.0819491 3.4329475
## 114 2.5785119 0.2413864 2.9211347 0.5446127 1.2118306 0.7241592 2.9211347
## 115 0.6865895 3.0896528 0.3432948 2.7639228 2.0597685 2.7715335 0.3432948
## 116 2.2844497 0.5446127 2.6200532 0.2413864 0.9959227 0.8733511 2.6200532
## 117 3.0896528 0.6865895 3.4329475 1.0892254 1.7164738 1.0819491 3.4329475
## 118 1.3731790 1.0298843 1.7164738 0.7641926 0.0000000 0.7710528 1.7164738
## 119 4.4628318 2.0597685 4.8061265 2.4312539 3.0896528 2.4236611 4.8061265
## 120 1.7164738 0.6865895 2.0597685 0.4827728 0.3432948 0.4881963 2.0597685
## 121 2.9438642 1.0892254 3.2676761 1.5421057 1.7256530 0.9763925 3.2676761
## 22 23 24 25 26 27 28
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23 1.5524262
## 24 1.3731790 0.2413864
## 25 2.4030633 0.8771115 1.0298843
## 26 1.7164738 0.2440981 0.3432948 0.6865895
## 27 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119
## 28 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119 0.0000000
## 29 2.9249630 1.4191561 1.5562377 0.5446127 1.2156269 1.4117152 1.4117152
## 30 3.7762423 2.2399190 2.4030633 1.3731790 2.0597685 0.5409745 0.5409745
## 31 3.0896528 1.5562377 1.7164738 0.6865895 1.3731790 1.2118306 1.2118306
## 32 1.5524262 0.0000000 0.2413864 0.8771115 0.2440981 2.7463580 2.7463580
## 33 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 34 3.6105942 2.0919598 2.2399190 1.2156269 1.8978159 0.7641926 0.7641926
## 35 4.1299928 2.5785119 2.7639228 1.7467021 2.4236611 0.2440981 0.2440981
## 36 0.7641926 0.8771115 0.7710528 1.7542231 1.0892254 3.6105942 3.6105942
## 37 1.8939967 0.3432948 0.5409745 0.5446127 0.2413864 2.4030633 2.4030633
## 38 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 39 2.2360953 0.6865895 0.8733511 0.2440981 0.5409745 2.0597685 2.0597685
## 40 0.5446127 2.0597685 1.8978159 2.9249630 2.2399190 4.8061265 4.8061265
## 41 0.2413864 1.3731790 1.2156269 2.2399190 1.5562377 4.1195370 4.1195370
## 42 2.7639228 1.2118306 1.4117152 0.4827728 1.0819491 1.5562377 1.5562377
## 43 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 44 1.2118306 0.3432948 0.2440981 1.2156269 0.5446127 3.0896528 3.0896528
## 45 0.7641926 0.8771115 0.7710528 1.7542231 1.0892254 3.6105942 3.6105942
## 46 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 47 1.2118306 0.3432948 0.2440981 1.2156269 0.5446127 3.0896528 3.0896528
## 48 1.0819491 0.5446127 0.4881963 1.4191561 0.7710528 3.2677283 3.2677283
## 49 3.1124753 1.6338381 1.7542231 0.7710528 1.4191561 1.3019294 1.3019294
## 50 0.3432948 1.8939967 1.7164738 2.7463580 2.0597685 4.6357401 4.6357401
## 51 2.5785119 1.0298843 1.2118306 0.2413864 0.8733511 1.7164738 1.7164738
## 52 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 53 0.2413864 1.3731790 1.2156269 2.2399190 1.5562377 4.1195370 4.1195370
## 54 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 55 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119 0.0000000 0.0000000
## 56 2.5785119 1.0298843 1.2118306 0.2413864 0.8733511 1.7164738 1.7164738
## 57 0.5446127 2.0597685 1.8978159 2.9249630 2.2399190 4.8061265 4.8061265
## 58 1.7467021 0.2413864 0.4827728 0.7710528 0.3432948 2.5823384 2.5823384
## 59 0.7710528 0.9959227 0.7641926 1.7467021 1.0819491 3.6354917 3.6354917
## 60 1.7542231 0.5446127 0.4881963 0.7641926 0.3432948 2.6200532 2.6200532
## 61 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 62 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119 0.0000000 0.0000000
## 63 2.4030633 0.8771115 1.0298843 0.0000000 0.6865895 1.8939967 1.8939967
## 64 0.0000000 1.5524262 1.3731790 2.4030633 1.7164738 4.2926996 4.2926996
## 65 4.1299928 2.5785119 2.7639228 1.7467021 2.4236611 0.2440981 0.2440981
## 66 3.2960163 1.7467021 1.9515236 0.9959227 1.6229236 1.0892254 1.0892254
## 67 3.6105942 2.0919598 2.2399190 1.2156269 1.8978159 0.7641926 0.7641926
## 68 4.1299928 2.5785119 2.7639228 1.7467021 2.4236611 0.2440981 0.2440981
## 69 3.4462515 1.8939967 2.0843943 1.0819491 1.7467021 0.8771115 0.8771115
## 70 2.5785119 1.0298843 1.2118306 0.2413864 0.8733511 1.7164738 1.7164738
## 71 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 72 3.2677283 1.7542231 1.8978159 0.8771115 1.5562377 1.0819491 1.0819491
## 73 2.4030633 0.8771115 1.0298843 0.0000000 0.6865895 1.8939967 1.8939967
## 74 0.6865895 0.8733511 0.6865895 1.7164738 1.0298843 3.6067636 3.6067636
## 75 3.4462515 1.8939967 2.0843943 1.0819491 1.7467021 0.8771115 0.8771115
## 76 2.5785119 1.0298843 1.2118306 0.2413864 0.8733511 1.7164738 1.7164738
## 77 1.3019294 0.4881963 0.5446127 1.3125041 0.7322944 3.1124753 3.1124753
## 78 3.0896528 1.5562377 1.7164738 0.6865895 1.3731790 1.2118306 1.2118306
## 79 2.2360953 0.6865895 0.8733511 0.2440981 0.5409745 2.0597685 2.0597685
## 80 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 81 0.6865895 2.2360953 2.0597685 3.0896528 2.4030633 4.9788157 4.9788157
## 82 1.8415638 0.5409745 0.7641926 0.9763925 0.6865895 2.6313346 2.6313346
## 83 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 84 1.5524262 0.0000000 0.2413864 0.8771115 0.2440981 2.7463580 2.7463580
## 85 2.2360953 0.6865895 0.8733511 0.2440981 0.5409745 2.0597685 2.0597685
## 86 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 87 0.3432948 1.5562377 1.4191561 2.4312539 1.7542231 4.2965315 4.2965315
## 88 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 89 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119 0.0000000 0.0000000
## 90 2.7463580 1.2156269 1.3731790 0.3432948 1.0298843 1.5524262 1.5524262
## 91 0.2440981 1.7164738 1.5562377 2.5823384 1.8978159 4.4628318 4.4628318
## 92 3.5730658 2.0652767 2.2925779 1.4483183 1.9918455 1.2204907 1.2204907
## 93 3.2638987 1.7164738 1.8939967 0.8733511 1.5524262 1.0298843 1.0298843
## 94 0.5409745 1.0298843 0.8771115 1.8978159 1.2156269 3.7762423 3.7762423
## 95 3.4462515 1.8939967 2.0843943 1.0819491 1.7467021 0.8771115 0.8771115
## 96 1.2118306 0.3432948 0.2440981 1.2156269 0.5446127 3.0896528 3.0896528
## 97 1.4117152 0.2440981 0.3432948 1.0892254 0.4881963 2.9249630 2.9249630
## 98 2.9211347 1.3731790 1.5524262 0.5409745 1.2118306 1.3731790 1.3731790
## 99 1.5524262 0.0000000 0.2413864 0.8771115 0.2440981 2.7463580 2.7463580
## 100 2.2360953 0.6865895 0.8733511 0.2440981 0.5409745 2.0597685 2.0597685
## 101 3.2677283 1.7542231 1.8978159 0.8771115 1.5562377 1.0819491 1.0819491
## 102 0.6865895 2.2360953 2.0597685 3.0896528 2.4030633 4.9788157 4.9788157
## 103 1.2118306 0.3432948 0.2440981 1.2156269 0.5446127 3.0896528 3.0896528
## 104 2.2360953 0.6865895 0.8733511 0.2440981 0.5409745 2.0597685 2.0597685
## 105 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 106 4.2926996 2.7463580 2.9211347 1.8939967 2.5785119 0.0000000 0.0000000
## 107 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 108 2.5823384 1.0892254 1.2156269 0.2440981 0.8771115 1.7467021 1.7467021
## 109 0.8733511 0.6865895 0.5446127 1.5562377 0.8771115 3.4329475 3.4329475
## 110 0.2413864 1.7467021 1.5524262 2.5785119 1.8939967 4.4721907 4.4721907
## 111 0.2413864 1.3731790 1.2156269 2.2399190 1.5562377 4.1195370 4.1195370
## 112 0.2440981 1.7164738 1.5562377 2.5823384 1.8978159 4.4628318 4.4628318
## 113 0.2413864 1.3731790 1.2156269 2.2399190 1.5562377 4.1195370 4.1195370
## 114 0.6865895 0.8733511 0.6865895 1.7164738 1.0298843 3.6067636 3.6067636
## 115 3.9497032 2.4030633 2.5785119 1.5524262 2.2360953 0.3432948 0.3432948
## 116 1.0892254 0.7241592 0.4827728 1.4117152 0.7641926 3.2960163 3.2960163
## 117 0.2413864 1.3731790 1.2156269 2.2399190 1.5562377 4.1195370 4.1195370
## 118 1.8939967 0.3432948 0.5409745 0.5446127 0.2413864 2.4030633 2.4030633
## 119 1.2156269 2.7463580 2.5823384 3.6105942 2.9249630 5.4927160 5.4927160
## 120 1.5524262 0.0000000 0.2413864 0.8771115 0.2440981 2.7463580 2.7463580
## 121 1.3019294 1.4645888 1.4843476 2.2493033 1.7086869 3.9252461 3.9252461
## 29 30 31 32 33 34 35
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30 0.8733511
## 31 0.2413864 0.6865895
## 32 1.4191561 2.2399190 1.5562377
## 33 0.3432948 0.8771115 0.2440981 1.3731790
## 34 0.6865895 0.2413864 0.5446127 2.0919598 0.7710528
## 35 1.3019294 0.4827728 1.0819491 2.5785119 1.2118306 0.7241592
## 36 2.2956598 3.1124753 2.4312539 0.8771115 2.2399190 2.9687526 3.4329475
## 37 1.0892254 1.8978159 1.2156269 0.3432948 1.0298843 1.7542231 2.2360953
## 38 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 39 0.7710528 1.5562377 0.8771115 0.6865895 0.6865895 1.4191561 1.8939967
## 40 3.4538833 4.2965315 3.6105942 2.0597685 3.4329475 4.1376361 4.6357401
## 41 2.7715335 3.6105942 2.9249630 1.3731790 2.7463580 3.4538833 3.9497032
## 42 0.5446127 1.0892254 0.4881963 1.2118306 0.2440981 1.0057881 1.3731790
## 43 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 44 1.7542231 2.5823384 1.8978159 0.3432948 1.7164738 2.4312539 2.9211347
## 45 2.2956598 3.1124753 2.4312539 0.8771115 2.2399190 2.9687526 3.4329475
## 46 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 47 1.7542231 2.5823384 1.8978159 0.3432948 1.7164738 2.4312539 2.9211347
## 48 1.9626230 2.7715335 2.0919598 0.5446127 1.8978159 2.6313346 3.0896528
## 49 0.2440981 0.7641926 0.3432948 1.6338381 0.5446127 0.5409745 1.2313686
## 50 3.2677283 4.1195370 3.4329475 1.8939967 3.2638987 3.9535345 4.4721907
## 51 0.4881963 1.2156269 0.5446127 1.0298843 0.3432948 1.0892254 1.5524262
## 52 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 53 2.7715335 3.6105942 2.9249630 1.3731790 2.7463580 3.4538833 3.9497032
## 54 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 55 1.4117152 0.5409745 1.2118306 2.7463580 1.3731790 0.7641926 0.2440981
## 56 0.4881963 1.2156269 0.5446127 1.0298843 0.3432948 1.0892254 1.5524262
## 57 3.4538833 4.2965315 3.6105942 2.0597685 3.4329475 4.1376361 4.6357401
## 58 1.3125041 2.0919598 1.4191561 0.2413864 1.2156269 1.9626230 2.4030633
## 59 2.2360953 3.1048524 2.4236611 0.9959227 2.2844497 2.9211347 3.4934043
## 60 1.2118306 2.0843943 1.4117152 0.5446127 1.3019294 1.8939967 2.4918378
## 61 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 62 1.4117152 0.5409745 1.2118306 2.7463580 1.3731790 0.7641926 0.2440981
## 63 0.5446127 1.3731790 0.6865895 0.8771115 0.5409745 1.2156269 1.7467021
## 64 2.9249630 3.7762423 3.0896528 1.5524262 2.9211347 3.6105942 4.1299928
## 65 1.3019294 0.4827728 1.0819491 2.5785119 1.2118306 0.7241592 0.0000000
## 66 0.7641926 0.7322944 0.5409745 1.7467021 0.4827728 0.7710528 0.8771115
## 67 0.6865895 0.2413864 0.5446127 2.0919598 0.7710528 0.0000000 0.7241592
## 68 1.3019294 0.4827728 1.0819491 2.5785119 1.2118306 0.7241592 0.0000000
## 69 0.7241592 0.4881963 0.4827728 1.8939967 0.5409745 0.5446127 0.6865895
## 70 0.4881963 1.2156269 0.5446127 1.0298843 0.3432948 1.0892254 1.5524262
## 71 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 72 0.3432948 0.5409745 0.2440981 1.7542231 0.4881963 0.3432948 0.9959227
## 73 0.5446127 1.3731790 0.6865895 0.8771115 0.5409745 1.2156269 1.7467021
## 74 2.2399190 3.0896528 2.4030633 0.8733511 2.2360953 2.9249630 3.4462515
## 75 0.7241592 0.4881963 0.4827728 1.8939967 0.5409745 0.5446127 0.6865895
## 76 0.4881963 1.2156269 0.5446127 1.0298843 0.3432948 1.0892254 1.5524262
## 77 1.8558064 2.6313346 1.9626230 0.4881963 1.7542231 2.5065874 2.9249630
## 78 0.2413864 0.6865895 0.0000000 1.5562377 0.2440981 0.5446127 1.0819491
## 79 0.7710528 1.5562377 0.8771115 0.6865895 0.6865895 1.4191561 1.8939967
## 80 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 81 3.6105942 4.4628318 3.7762423 2.2360953 3.6067636 4.2965315 4.8145447
## 82 1.4843476 2.1784507 1.5421057 0.5409745 1.3125041 2.0827328 2.4312539
## 83 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 84 1.4191561 2.2399190 1.5562377 0.0000000 1.3731790 2.0919598 2.5785119
## 85 0.7710528 1.5562377 0.8771115 0.6865895 0.6865895 1.4191561 1.8939967
## 86 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 87 2.9687526 3.7956317 3.1124753 1.5562377 2.9249630 3.6468808 4.1195370
## 88 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 89 1.4117152 0.5409745 1.2118306 2.7463580 1.3731790 0.7641926 0.2440981
## 90 0.2440981 1.0298843 0.3432948 1.2156269 0.2413864 0.8771115 1.4117152
## 91 3.1124753 3.9535345 3.2677283 1.7164738 3.0896528 3.7956317 4.2926996
## 92 1.3019294 1.0892254 1.0819491 2.0652767 0.9959227 1.2156269 0.9763925
## 93 0.4827728 0.5446127 0.2413864 1.7164738 0.3432948 0.4881963 0.8733511
## 94 2.4312539 3.2677283 2.5823384 1.0298843 2.4030633 3.1124753 3.6067636
## 95 0.7241592 0.4881963 0.4827728 1.8939967 0.5409745 0.5446127 0.6865895
## 96 1.7542231 2.5823384 1.8978159 0.3432948 1.7164738 2.4312539 2.9211347
## 97 1.6338381 2.4312539 1.7542231 0.2440981 1.5562377 2.2956598 2.7463580
## 98 0.3432948 0.8771115 0.2440981 1.3731790 0.0000000 0.7710528 1.2118306
## 99 1.4191561 2.2399190 1.5562377 0.0000000 1.3731790 2.0919598 2.5785119
## 100 0.7710528 1.5562377 0.8771115 0.6865895 0.6865895 1.4191561 1.8939967
## 101 0.3432948 0.5409745 0.2440981 1.7542231 0.4881963 0.3432948 0.9959227
## 102 3.6105942 4.4628318 3.7762423 2.2360953 3.6067636 4.2965315 4.8145447
## 103 1.7542231 2.5823384 1.8978159 0.3432948 1.7164738 2.4312539 2.9211347
## 104 0.7710528 1.5562377 0.8771115 0.6865895 0.6865895 1.4191561 1.8939967
## 105 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 106 1.4117152 0.5409745 1.2118306 2.7463580 1.3731790 0.7641926 0.2440981
## 107 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 108 0.3432948 1.2118306 0.5409745 1.0892254 0.4827728 1.0298843 1.6229236
## 109 2.0919598 2.9249630 2.2399190 0.6865895 2.0597685 2.7715335 3.2638987
## 110 3.0896528 3.9497032 3.2638987 1.7467021 3.1048524 3.7762423 4.3162553
## 111 2.7715335 3.6105942 2.9249630 1.3731790 2.7463580 3.4538833 3.9497032
## 112 3.1124753 3.9535345 3.2677283 1.7164738 3.0896528 3.7956317 4.2926996
## 113 2.7715335 3.6105942 2.9249630 1.3731790 2.7463580 3.4538833 3.9497032
## 114 2.2399190 3.0896528 2.4030633 0.8733511 2.2360953 2.9249630 3.4462515
## 115 1.0819491 0.2413864 0.8733511 2.4030633 1.0298843 0.4827728 0.2413864
## 116 1.8939967 2.7639228 2.0843943 0.7241592 1.9515236 2.5785119 3.1575251
## 117 2.7715335 3.6105942 2.9249630 1.3731790 2.7463580 3.4538833 3.9497032
## 118 1.0892254 1.8978159 1.2156269 0.3432948 1.0298843 1.7542231 2.2360953
## 119 4.1376361 4.9826484 4.2965315 2.7463580 4.1195370 4.8221951 5.3219196
## 120 1.4191561 2.2399190 1.5562377 0.0000000 1.3731790 2.0919598 2.5785119
## 121 2.7810175 3.4881664 2.8534067 1.4645888 2.6250082 3.3950498 3.7146725
## 36 37 38 39 40 41 42
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35
## 36
## 37 1.2156269
## 38 2.2399190 1.0298843
## 39 1.5562377 0.3432948 0.6865895
## 40 1.2118306 2.4030633 3.4329475 2.7463580
## 41 0.5409745 1.7164738 2.7463580 2.0597685 0.6865895
## 42 2.0597685 0.8733511 0.2440981 0.5409745 3.2638987 2.5785119
## 43 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 44 0.5446127 0.6865895 1.7164738 1.0298843 1.7164738 1.0298843 1.5524262
## 45 0.0000000 1.2156269 2.2399190 1.5562377 1.2118306 0.5409745 2.0597685
## 46 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 47 0.5446127 0.6865895 1.7164738 1.0298843 1.7164738 1.0298843 1.5524262
## 48 0.3432948 0.8771115 1.8978159 1.2156269 1.5524262 0.8733511 1.7164738
## 49 2.5065874 1.3125041 0.5446127 1.0057881 3.6468808 2.9687526 0.7710528
## 50 1.0819491 2.2360953 3.2638987 2.5785119 0.2440981 0.5409745 3.1048524
## 51 1.8978159 0.6865895 0.3432948 0.3432948 3.0896528 2.4030633 0.2413864
## 52 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 53 0.5409745 1.7164738 2.7463580 2.0597685 0.6865895 0.0000000 2.5785119
## 54 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 55 3.6105942 2.4030633 1.3731790 2.0597685 4.8061265 4.1195370 1.5562377
## 56 1.8978159 0.6865895 0.3432948 0.3432948 3.0896528 2.4030633 0.2413864
## 57 1.2118306 2.4030633 3.4329475 2.7463580 0.0000000 0.6865895 3.2638987
## 58 1.0298843 0.2440981 1.2156269 0.5446127 2.2360953 1.5524262 1.0298843
## 59 0.6865895 1.3019294 2.2844497 1.6229236 1.3125041 0.7322944 2.1638981
## 60 1.2441322 0.5409745 1.3019294 0.7241592 2.2956598 1.6338381 1.2313686
## 61 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 62 3.6105942 2.4030633 1.3731790 2.0597685 4.8061265 4.1195370 1.5562377
## 63 1.7542231 0.5446127 0.5409745 0.2440981 2.9249630 2.2399190 0.4827728
## 64 0.7641926 1.8939967 2.9211347 2.2360953 0.5446127 0.2413864 2.7639228
## 65 3.4329475 2.2360953 1.2118306 1.8939967 4.6357401 3.9497032 1.3731790
## 66 2.5785119 1.4117152 0.4827728 1.0819491 3.7879933 3.1048524 0.5409745
## 67 2.9687526 1.7542231 0.7710528 1.4191561 4.1376361 3.4538833 1.0057881
## 68 3.4329475 2.2360953 1.2118306 1.8939967 4.6357401 3.9497032 1.3731790
## 69 2.7463580 1.5524262 0.5409745 1.2118306 3.9497032 3.2638987 0.6865895
## 70 1.8978159 0.6865895 0.3432948 0.3432948 3.0896528 2.4030633 0.2413864
## 71 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 72 2.6313346 1.4191561 0.4881963 1.0892254 3.7956317 3.1124753 0.7322944
## 73 1.7542231 0.5446127 0.5409745 0.2440981 2.9249630 2.2399190 0.4827728
## 74 0.3432948 1.2118306 2.2360953 1.5524262 1.2156269 0.5446127 2.0843943
## 75 2.7463580 1.5524262 0.5409745 1.2118306 3.9497032 3.2638987 0.6865895
## 76 1.8978159 0.6865895 0.3432948 0.3432948 3.0896528 2.4030633 0.2413864
## 77 0.5409745 0.7710528 1.7542231 1.0892254 1.7467021 1.0819491 1.5562377
## 78 2.4312539 1.2156269 0.2440981 0.8771115 3.6105942 2.9249630 0.4881963
## 79 1.5562377 0.3432948 0.6865895 0.0000000 2.7463580 2.0597685 0.5409745
## 80 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 81 1.4117152 2.5785119 3.6067636 2.9211347 0.2413864 0.8733511 3.4462515
## 82 1.0819491 0.5446127 1.3125041 0.7322944 2.2844497 1.6229236 1.0892254
## 83 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 84 0.8771115 0.3432948 1.3731790 0.6865895 2.0597685 1.3731790 1.2118306
## 85 1.5562377 0.3432948 0.6865895 0.0000000 2.7463580 2.0597685 0.5409745
## 86 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 87 0.6865895 1.8978159 2.9249630 2.2399190 0.5409745 0.2440981 2.7463580
## 88 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 89 3.6105942 2.4030633 1.3731790 2.0597685 4.8061265 4.1195370 1.5562377
## 90 2.0919598 0.8771115 0.2413864 0.5446127 3.2677283 2.5823384 0.3432948
## 91 0.8733511 2.0597685 3.0896528 2.4030633 0.3432948 0.3432948 2.9211347
## 92 2.8234304 1.7588171 0.9959227 1.4687443 4.0307200 3.3630514 0.9655455
## 93 2.5823384 1.3731790 0.3432948 1.0298843 3.7762423 3.0896528 0.5446127
## 94 0.2413864 1.3731790 2.4030633 1.7164738 1.0298843 0.3432948 2.2360953
## 95 2.7463580 1.5524262 0.5409745 1.2118306 3.9497032 3.2638987 0.6865895
## 96 0.5446127 0.6865895 1.7164738 1.0298843 1.7164738 1.0298843 1.5524262
## 97 0.6865895 0.5446127 1.5562377 0.8771115 1.8939967 1.2118306 1.3731790
## 98 2.2399190 1.0298843 0.0000000 0.6865895 3.4329475 2.7463580 0.2440981
## 99 0.8771115 0.3432948 1.3731790 0.6865895 2.0597685 1.3731790 1.2118306
## 100 1.5562377 0.3432948 0.6865895 0.0000000 2.7463580 2.0597685 0.5409745
## 101 2.6313346 1.4191561 0.4881963 1.0892254 3.7956317 3.1124753 0.7322944
## 102 1.4117152 2.5785119 3.6067636 2.9211347 0.2413864 0.8733511 3.4462515
## 103 0.5446127 0.6865895 1.7164738 1.0298843 1.7164738 1.0298843 1.5524262
## 104 1.5562377 0.3432948 0.6865895 0.0000000 2.7463580 2.0597685 0.5409745
## 105 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 106 3.6105942 2.4030633 1.3731790 2.0597685 4.8061265 4.1195370 1.5562377
## 107 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 108 1.9626230 0.7710528 0.4827728 0.4881963 3.1124753 2.4312539 0.5409745
## 109 0.2440981 1.0298843 2.0597685 1.3731790 1.3731790 0.6865895 1.8939967
## 110 0.9959227 2.0843943 3.1048524 2.4236611 0.4881963 0.4827728 2.9574228
## 111 0.5409745 1.7164738 2.7463580 2.0597685 0.6865895 0.0000000 2.5785119
## 112 0.8733511 2.0597685 3.0896528 2.4030633 0.3432948 0.3432948 2.9211347
## 113 0.5409745 1.7164738 2.7463580 2.0597685 0.6865895 0.0000000 2.5785119
## 114 0.3432948 1.2118306 2.2360953 1.5524262 1.2156269 0.5446127 2.0843943
## 115 3.2677283 2.0597685 1.0298843 1.7164738 4.4628318 3.7762423 1.2156269
## 116 0.7710528 0.9959227 1.9515236 1.3019294 1.6338381 1.0057881 1.8415638
## 117 0.5409745 1.7164738 2.7463580 2.0597685 0.6865895 0.0000000 2.5785119
## 118 1.2156269 0.0000000 1.0298843 0.3432948 2.4030633 1.7164738 0.8733511
## 119 1.8939967 3.0896528 4.1195370 3.4329475 0.6865895 1.3731790 3.9497032
## 120 0.8771115 0.3432948 1.3731790 0.6865895 2.0597685 1.3731790 1.2118306
## 121 0.8771115 1.7256530 2.6250082 2.0115762 1.4483183 1.0819491 2.3997029
## 43 44 45 46 47 48 49
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35
## 36
## 37
## 38
## 39
## 40
## 41
## 42
## 43
## 44 0.3432948
## 45 0.2440981 0.5446127
## 46 2.0597685 1.7164738 2.2399190
## 47 0.3432948 0.0000000 0.5446127 1.7164738
## 48 0.2413864 0.2440981 0.3432948 1.8978159 0.2440981
## 49 2.2956598 1.9626230 2.5065874 0.5446127 1.9626230 2.1784507
## 50 1.2118306 1.5524262 1.0819491 3.2638987 1.5524262 1.4117152 3.4538833
## 51 1.7164738 1.3731790 1.8978159 0.3432948 1.3731790 1.5562377 0.7322944
## 52 2.0597685 1.7164738 2.2399190 0.0000000 1.7164738 1.8978159 0.5446127
## 53 0.6865895 1.0298843 0.5409745 2.7463580 1.0298843 0.8733511 2.9687526
## 54 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 55 3.4329475 3.0896528 3.6105942 1.3731790 3.0896528 3.2677283 1.3019294
## 56 1.7164738 1.3731790 1.8978159 0.3432948 1.3731790 1.5562377 0.7322944
## 57 1.3731790 1.7164738 1.2118306 3.4329475 1.7164738 1.5524262 3.6468808
## 58 0.8733511 0.5409745 1.0298843 1.2156269 0.5409745 0.6865895 1.5421057
## 59 0.5409745 0.7241592 0.6865895 2.2844497 0.7241592 0.7641926 2.4030633
## 60 1.0057881 0.7322944 1.2441322 1.3019294 0.7322944 0.9763925 1.3731790
## 61 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 62 3.4329475 3.0896528 3.6105942 1.3731790 3.0896528 3.2677283 1.3019294
## 63 1.5562377 1.2156269 1.7542231 0.5409745 1.2156269 1.4191561 0.7710528
## 64 0.8733511 1.2118306 0.7641926 2.9211347 1.2118306 1.0819491 3.1124753
## 65 3.2638987 2.9211347 3.4329475 1.2118306 2.9211347 3.0896528 1.2313686
## 66 2.4236611 2.0843943 2.5785119 0.4827728 2.0843943 2.2360953 0.8733511
## 67 2.7715335 2.4312539 2.9687526 0.7710528 2.4312539 2.6313346 0.5409745
## 68 3.2638987 2.9211347 3.4329475 1.2118306 2.9211347 3.0896528 1.2313686
## 69 2.5785119 2.2360953 2.7463580 0.5409745 2.2360953 2.4030633 0.7641926
## 70 1.7164738 1.3731790 1.8978159 0.3432948 1.3731790 1.5562377 0.7322944
## 71 2.0597685 1.7164738 2.2399190 0.0000000 1.7164738 1.8978159 0.5446127
## 72 2.4312539 2.0919598 2.6313346 0.4881963 2.0919598 2.2956598 0.2413864
## 73 1.5562377 1.2156269 1.7542231 0.5409745 1.2156269 1.4191561 0.7710528
## 74 0.2413864 0.5409745 0.3432948 2.2360953 0.5409745 0.4827728 2.4312539
## 75 2.5785119 2.2360953 2.7463580 0.5409745 2.2360953 2.4030633 0.7641926
## 76 1.7164738 1.3731790 1.8978159 0.3432948 1.3731790 1.5562377 0.7322944
## 77 0.4827728 0.3432948 0.5409745 1.7542231 0.3432948 0.2413864 2.0827328
## 78 2.2399190 1.8978159 2.4312539 0.2440981 1.8978159 2.0919598 0.3432948
## 79 1.3731790 1.0298843 1.5562377 0.6865895 1.0298843 1.2156269 1.0057881
## 80 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 81 1.5524262 1.8939967 1.4117152 3.6067636 1.8939967 1.7467021 3.7956317
## 82 0.9959227 0.7241592 1.0819491 1.3125041 0.7241592 0.7641926 1.7256530
## 83 2.0597685 1.7164738 2.2399190 0.0000000 1.7164738 1.8978159 0.5446127
## 84 0.6865895 0.3432948 0.8771115 1.3731790 0.3432948 0.5446127 1.6338381
## 85 1.3731790 1.0298843 1.5562377 0.6865895 1.0298843 1.2156269 1.0057881
## 86 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 87 0.8771115 1.2156269 0.6865895 2.9249630 1.2156269 1.0298843 3.1724996
## 88 2.0597685 1.7164738 2.2399190 0.0000000 1.7164738 1.8978159 0.5446127
## 89 3.4329475 3.0896528 3.6105942 1.3731790 3.0896528 3.2677283 1.3019294
## 90 1.8978159 1.5562377 2.0919598 0.2413864 1.5562377 1.7542231 0.4881963
## 91 1.0298843 1.3731790 0.8733511 3.0896528 1.3731790 1.2118306 3.3073803
## 92 2.7048727 2.3818062 2.8234304 0.9959227 2.3818062 2.4918378 1.4117152
## 93 2.4030633 2.0597685 2.5823384 0.3432948 2.0597685 2.2399190 0.5409745
## 94 0.3432948 0.6865895 0.2413864 2.4030633 0.6865895 0.5409745 2.6313346
## 95 2.5785119 2.2360953 2.7463580 0.5409745 2.2360953 2.4030633 0.7641926
## 96 0.3432948 0.0000000 0.5446127 1.7164738 0.0000000 0.2440981 1.9626230
## 97 0.5409745 0.2413864 0.6865895 1.5562377 0.2413864 0.3432948 1.8558064
## 98 2.0597685 1.7164738 2.2399190 0.0000000 1.7164738 1.8978159 0.5446127
## 99 0.6865895 0.3432948 0.8771115 1.3731790 0.3432948 0.5446127 1.6338381
## 100 1.3731790 1.0298843 1.5562377 0.6865895 1.0298843 1.2156269 1.0057881
## 101 2.4312539 2.0919598 2.6313346 0.4881963 2.0919598 2.2956598 0.2413864
## 102 1.5524262 1.8939967 1.4117152 3.6067636 1.8939967 1.7467021 3.7956317
## 103 0.3432948 0.0000000 0.5446127 1.7164738 0.0000000 0.2440981 1.9626230
## 104 1.3731790 1.0298843 1.5562377 0.6865895 1.0298843 1.2156269 1.0057881
## 105 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 106 3.4329475 3.0896528 3.6105942 1.3731790 3.0896528 3.2677283 1.3019294
## 107 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 108 1.7542231 1.4191561 1.9626230 0.4827728 1.4191561 1.6338381 0.5446127
## 109 0.0000000 0.3432948 0.2440981 2.0597685 0.3432948 0.2413864 2.2956598
## 110 1.0819491 1.4117152 0.9959227 3.1048524 1.4117152 1.3019294 3.2677283
## 111 0.6865895 1.0298843 0.5409745 2.7463580 1.0298843 0.8733511 2.9687526
## 112 1.0298843 1.3731790 0.8733511 3.0896528 1.3731790 1.2118306 3.3073803
## 113 0.6865895 1.0298843 0.5409745 2.7463580 1.0298843 0.8733511 2.9687526
## 114 0.2413864 0.5409745 0.3432948 2.2360953 0.5409745 0.4827728 2.4312539
## 115 3.0896528 2.7463580 3.2677283 1.0298843 2.7463580 2.9249630 0.9959227
## 116 0.5446127 0.5409745 0.7710528 1.9515236 0.5409745 0.6865895 2.0597685
## 117 0.6865895 1.0298843 0.5409745 2.7463580 1.0298843 0.8733511 2.9687526
## 118 1.0298843 0.6865895 1.2156269 1.0298843 0.6865895 0.8771115 1.3125041
## 119 2.0597685 2.4030633 1.8939967 4.1195370 2.4030633 2.2360953 4.3276781
## 120 0.6865895 0.3432948 0.8771115 1.3731790 0.3432948 0.5446127 1.6338381
## 121 1.0892254 1.2441322 0.8771115 2.6250082 1.2441322 1.0057881 3.0173644
## 50 51 52 53 54 55 56
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35
## 36
## 37
## 38
## 39
## 40
## 41
## 42
## 43
## 44
## 45
## 46
## 47
## 48
## 49
## 50
## 51 2.9211347
## 52 3.2638987 0.3432948
## 53 0.5409745 2.4030633 2.7463580
## 54 1.2118306 1.7164738 2.0597685 0.6865895
## 55 4.6357401 1.7164738 1.3731790 4.1195370 3.4329475
## 56 2.9211347 0.0000000 0.3432948 2.4030633 1.7164738 1.7164738
## 57 0.2440981 3.0896528 3.4329475 0.6865895 1.3731790 4.8061265 3.0896528
## 58 2.0843943 0.8771115 1.2156269 1.5524262 0.8733511 2.5823384 0.8771115
## 59 1.0892254 1.9515236 2.2844497 0.7322944 0.5409745 3.6354917 1.9515236
## 60 2.0919598 0.9959227 1.3019294 1.6338381 1.0057881 2.6200532 0.9959227
## 61 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 62 4.6357401 1.7164738 1.3731790 4.1195370 3.4329475 0.0000000 1.7164738
## 63 2.7463580 0.2413864 0.5409745 2.2399190 1.5562377 1.8939967 0.2413864
## 64 0.3432948 2.5785119 2.9211347 0.2413864 0.8733511 4.2926996 2.5785119
## 65 4.4721907 1.5524262 1.2118306 3.9497032 3.2638987 0.2440981 1.5524262
## 66 3.6354917 0.7641926 0.4827728 3.1048524 2.4236611 1.0892254 0.7641926
## 67 3.9535345 1.0892254 0.7710528 3.4538833 2.7715335 0.7641926 1.0892254
## 68 4.4721907 1.5524262 1.2118306 3.9497032 3.2638987 0.2440981 1.5524262
## 69 3.7879933 0.8733511 0.5409745 3.2638987 2.5785119 0.8771115 0.8733511
## 70 2.9211347 0.0000000 0.3432948 2.4030633 1.7164738 1.7164738 0.0000000
## 71 3.2638987 0.3432948 0.0000000 2.7463580 2.0597685 1.3731790 0.3432948
## 72 3.6105942 0.7710528 0.4881963 3.1124753 2.4312539 1.0819491 0.7710528
## 73 2.7463580 0.2413864 0.5409745 2.2399190 1.5562377 1.8939967 0.2413864
## 74 1.0298843 1.8939967 2.2360953 0.5446127 0.2413864 3.6067636 1.8939967
## 75 3.7879933 0.8733511 0.5409745 3.2638987 2.5785119 0.8771115 0.8733511
## 76 2.9211347 0.0000000 0.3432948 2.4030633 1.7164738 1.7164738 0.0000000
## 77 1.6229236 1.4191561 1.7542231 1.0819491 0.4827728 3.1124753 1.4191561
## 78 3.4329475 0.5446127 0.2440981 2.9249630 2.2399190 1.2118306 0.5446127
## 79 2.5785119 0.3432948 0.6865895 2.0597685 1.3731790 2.0597685 0.3432948
## 80 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 81 0.3432948 3.2638987 3.6067636 0.8733511 1.5524262 4.9788157 3.2638987
## 82 2.1638981 1.0057881 1.3125041 1.6229236 0.9959227 2.6313346 1.0057881
## 83 3.2638987 0.3432948 0.0000000 2.7463580 2.0597685 1.3731790 0.3432948
## 84 1.8939967 1.0298843 1.3731790 1.3731790 0.6865895 2.7463580 1.0298843
## 85 2.5785119 0.3432948 0.6865895 2.0597685 1.3731790 2.0597685 0.3432948
## 86 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 87 0.4827728 2.5823384 2.9249630 0.2440981 0.8771115 4.2965315 2.5823384
## 88 3.2638987 0.3432948 0.0000000 2.7463580 2.0597685 1.3731790 0.3432948
## 89 4.6357401 1.7164738 1.3731790 4.1195370 3.4329475 0.0000000 1.7164738
## 90 3.0896528 0.2440981 0.2413864 2.5823384 1.8978159 1.5524262 0.2440981
## 91 0.2413864 2.7463580 3.0896528 0.3432948 1.0298843 4.4628318 2.7463580
## 92 3.9030472 1.2069319 0.9959227 3.3630514 2.7048727 1.2204907 1.2069319
## 93 3.6067636 0.6865895 0.3432948 3.0896528 2.4030633 1.0298843 0.6865895
## 94 0.8733511 2.0597685 2.4030633 0.3432948 0.3432948 3.7762423 2.0597685
## 95 3.7879933 0.8733511 0.5409745 3.2638987 2.5785119 0.8771115 0.8733511
## 96 1.5524262 1.3731790 1.7164738 1.0298843 0.3432948 3.0896528 1.3731790
## 97 1.7467021 1.2156269 1.5562377 1.2118306 0.5409745 2.9249630 1.2156269
## 98 3.2638987 0.3432948 0.0000000 2.7463580 2.0597685 1.3731790 0.3432948
## 99 1.8939967 1.0298843 1.3731790 1.3731790 0.6865895 2.7463580 1.0298843
## 100 2.5785119 0.3432948 0.6865895 2.0597685 1.3731790 2.0597685 0.3432948
## 101 3.6105942 0.7710528 0.4881963 3.1124753 2.4312539 1.0819491 0.7710528
## 102 0.3432948 3.2638987 3.6067636 0.8733511 1.5524262 4.9788157 3.2638987
## 103 1.5524262 1.3731790 1.7164738 1.0298843 0.3432948 3.0896528 1.3731790
## 104 2.5785119 0.3432948 0.6865895 2.0597685 1.3731790 2.0597685 0.3432948
## 105 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 106 4.6357401 1.7164738 1.3731790 4.1195370 3.4329475 0.0000000 1.7164738
## 107 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 108 2.9249630 0.3432948 0.4827728 2.4312539 1.7542231 1.7467021 0.3432948
## 109 1.2118306 1.7164738 2.0597685 0.6865895 0.0000000 3.4329475 1.7164738
## 110 0.2440981 2.7639228 3.1048524 0.4827728 1.0819491 4.4721907 2.7639228
## 111 0.5409745 2.4030633 2.7463580 0.0000000 0.6865895 4.1195370 2.4030633
## 112 0.2413864 2.7463580 3.0896528 0.3432948 1.0298843 4.4628318 2.7463580
## 113 0.5409745 2.4030633 2.7463580 0.0000000 0.6865895 4.1195370 2.4030633
## 114 1.0298843 1.8939967 2.2360953 0.5446127 0.2413864 3.6067636 1.8939967
## 115 4.2926996 1.3731790 1.0298843 3.7762423 3.0896528 0.3432948 1.3731790
## 116 1.4191561 1.6229236 1.9515236 1.0057881 0.5446127 3.2960163 1.6229236
## 117 0.5409745 2.4030633 2.7463580 0.0000000 0.6865895 4.1195370 2.4030633
## 118 2.2360953 0.6865895 1.0298843 1.7164738 1.0298843 2.4030633 0.6865895
## 119 0.8771115 3.7762423 4.1195370 1.3731790 2.0597685 5.4927160 3.7762423
## 120 1.8939967 1.0298843 1.3731790 1.3731790 0.6865895 2.7463580 1.0298843
## 121 1.4687443 2.3131585 2.6250082 1.0819491 1.0892254 3.9252461 2.3131585
## 57 58 59 60 61 62 63
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
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## 58 2.2360953
## 59 1.3125041 1.2313686
## 60 2.2956598 0.6865895 1.0298843
## 61 1.3731790 0.8733511 0.5409745 1.0057881
## 62 4.8061265 2.5823384 3.6354917 2.6200532 3.4329475
## 63 2.9249630 0.7710528 1.7467021 0.7641926 1.5562377 1.8939967
## 64 0.5446127 1.7467021 0.7710528 1.7542231 0.8733511 4.2926996 2.4030633
## 65 4.6357401 2.4030633 3.4934043 2.4918378 3.2638987 0.2440981 1.7467021
## 66 3.7879933 1.5524262 2.7048727 1.7588171 2.4236611 1.0892254 0.9959227
## 67 4.1376361 1.9626230 2.9211347 1.8939967 2.7715335 0.7641926 1.2156269
## 68 4.6357401 2.4030633 3.4934043 2.4918378 3.2638987 0.2440981 1.7467021
## 69 3.9497032 1.7164738 2.8234304 1.8415638 2.5785119 0.8771115 1.0819491
## 70 3.0896528 0.8771115 1.9515236 0.9959227 1.7164738 1.7164738 0.2413864
## 71 3.4329475 1.2156269 2.2844497 1.3019294 2.0597685 1.3731790 0.5409745
## 72 3.7956317 1.6338381 2.5785119 1.5524262 2.4312539 1.0819491 0.8771115
## 73 2.9249630 0.7710528 1.7467021 0.7641926 1.5562377 1.8939967 0.0000000
## 74 1.2156269 1.0819491 0.3432948 1.0892254 0.2413864 3.6067636 1.7164738
## 75 3.9497032 1.7164738 2.8234304 1.8415638 2.5785119 0.8771115 1.0819491
## 76 3.0896528 0.8771115 1.9515236 0.9959227 1.7164738 1.7164738 0.2413864
## 77 1.7467021 0.5446127 0.9959227 1.0057881 0.4827728 3.1124753 1.3125041
## 78 3.6105942 1.4191561 2.4236611 1.4117152 2.2399190 1.2118306 0.6865895
## 79 2.7463580 0.5446127 1.6229236 0.7241592 1.3731790 2.0597685 0.2440981
## 80 1.3731790 0.8733511 0.5409745 1.0057881 0.0000000 3.4329475 1.5562377
## 81 0.2413864 2.4236611 1.4191561 2.4312539 1.5524262 4.9788157 3.0896528
## 82 2.2844497 0.3432948 1.4483183 1.0298843 0.9959227 2.6313346 0.9763925
## 83 3.4329475 1.2156269 2.2844497 1.3019294 2.0597685 1.3731790 0.5409745
## 84 2.0597685 0.2413864 0.9959227 0.5446127 0.6865895 2.7463580 0.8771115
## 85 2.7463580 0.5446127 1.6229236 0.7241592 1.3731790 2.0597685 0.2440981
## 86 1.3731790 0.8733511 0.5409745 1.0057881 0.0000000 3.4329475 1.5562377
## 87 0.5409745 1.7164738 0.9763925 1.8558064 0.8771115 4.2965315 2.4312539
## 88 3.4329475 1.2156269 2.2844497 1.3019294 2.0597685 1.3731790 0.5409745
## 89 4.8061265 2.5823384 3.6354917 2.6200532 3.4329475 0.0000000 1.8939967
## 90 3.2677283 1.0892254 2.0843943 1.0819491 1.8978159 1.5524262 0.3432948
## 91 0.3432948 1.8939967 1.0057881 1.9626230 1.0298843 4.4628318 2.5823384
## 92 4.0307200 1.8415638 3.0567706 2.1861478 2.7048727 1.2204907 1.4483183
## 93 3.7762423 1.5562377 2.6200532 1.6229236 2.4030633 1.0298843 0.8733511
## 94 1.0298843 1.2118306 0.5446127 1.3125041 0.3432948 3.7762423 1.8978159
## 95 3.9497032 1.7164738 2.8234304 1.8415638 2.5785119 0.8771115 1.0819491
## 96 1.7164738 0.5409745 0.7241592 0.7322944 0.3432948 3.0896528 1.2156269
## 97 1.8939967 0.3432948 0.9655455 0.7710528 0.5409745 2.9249630 1.0892254
## 98 3.4329475 1.2156269 2.2844497 1.3019294 2.0597685 1.3731790 0.5409745
## 99 2.0597685 0.2413864 0.9959227 0.5446127 0.6865895 2.7463580 0.8771115
## 100 2.7463580 0.5446127 1.6229236 0.7241592 1.3731790 2.0597685 0.2440981
## 101 3.7956317 1.6338381 2.5785119 1.5524262 2.4312539 1.0819491 0.8771115
## 102 0.2413864 2.4236611 1.4191561 2.4312539 1.5524262 4.9788157 3.0896528
## 103 1.7164738 0.5409745 0.7241592 0.7322944 0.3432948 3.0896528 1.2156269
## 104 2.7463580 0.5446127 1.6229236 0.7241592 1.3731790 2.0597685 0.2440981
## 105 1.3731790 0.8733511 0.5409745 1.0057881 0.0000000 3.4329475 1.5562377
## 106 4.8061265 2.5823384 3.6354917 2.6200532 3.4329475 0.0000000 1.8939967
## 107 1.3731790 0.8733511 0.5409745 1.0057881 0.0000000 3.4329475 1.5562377
## 108 3.1124753 1.0057881 1.8939967 0.8733511 1.7542231 1.7467021 0.2440981
## 109 1.3731790 0.8733511 0.5409745 1.0057881 0.0000000 3.4329475 1.5562377
## 110 0.4881963 1.9515236 0.8771115 1.8978159 1.0819491 4.4721907 2.5785119
## 111 0.6865895 1.5524262 0.7322944 1.6338381 0.6865895 4.1195370 2.2399190
## 112 0.3432948 1.8939967 1.0057881 1.9626230 1.0298843 4.4628318 2.5823384
## 113 0.6865895 1.5524262 0.7322944 1.6338381 0.6865895 4.1195370 2.2399190
## 114 1.2156269 1.0819491 0.3432948 1.0892254 0.2413864 3.6067636 1.7164738
## 115 4.4628318 2.2399190 3.2960163 2.2844497 3.0896528 0.3432948 1.5524262
## 116 1.6338381 0.9655455 0.3432948 0.6865895 0.5446127 3.2960163 1.4117152
## 117 0.6865895 1.5524262 0.7322944 1.6338381 0.6865895 4.1195370 2.2399190
## 118 2.4030633 0.2440981 1.3019294 0.5409745 1.0298843 2.4030633 0.5446127
## 119 0.6865895 2.9211347 1.9626230 2.9687526 2.0597685 5.4927160 3.6105942
## 120 2.0597685 0.2413864 0.9959227 0.5446127 0.6865895 2.7463580 0.8771115
## 121 1.4483183 1.4843476 1.5562377 1.9676475 1.0892254 3.9252461 2.2493033
## 64 65 66 67 68 69 70
## 2
## 3
## 4
## 5
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## 63
## 64
## 65 4.1299928
## 66 3.2960163 0.8771115
## 67 3.6105942 0.7241592 0.7710528
## 68 4.1299928 0.0000000 0.8771115 0.7241592
## 69 3.4462515 0.6865895 0.2440981 0.5446127 0.6865895
## 70 2.5785119 1.5524262 0.7641926 1.0892254 1.5524262 0.8733511
## 71 2.9211347 1.2118306 0.4827728 0.7710528 1.2118306 0.5409745 0.3432948
## 72 3.2677283 0.9959227 0.6865895 0.3432948 0.9959227 0.5409745 0.7710528
## 73 2.4030633 1.7467021 0.9959227 1.2156269 1.7467021 1.0819491 0.2413864
## 74 0.6865895 3.4462515 2.6200532 2.9249630 3.4462515 2.7639228 1.8939967
## 75 3.4462515 0.6865895 0.2440981 0.5446127 0.6865895 0.0000000 0.8733511
## 76 2.5785119 1.5524262 0.7641926 1.0892254 1.5524262 0.8733511 0.0000000
## 77 1.3019294 2.9249630 2.0597685 2.5065874 2.9249630 2.2399190 1.4191561
## 78 3.0896528 1.0819491 0.5409745 0.5446127 1.0819491 0.4827728 0.5446127
## 79 2.2360953 1.8939967 1.0819491 1.4191561 1.8939967 1.2118306 0.3432948
## 80 0.8733511 3.2638987 2.4236611 2.7715335 3.2638987 2.5785119 1.7164738
## 81 0.6865895 4.8145447 3.9756230 4.2965315 4.8145447 4.1299928 3.2638987
## 82 1.8415638 2.4312539 1.5562377 2.0827328 2.4312539 1.7542231 1.0057881
## 83 2.9211347 1.2118306 0.4827728 0.7710528 1.2118306 0.5409745 0.3432948
## 84 1.5524262 2.5785119 1.7467021 2.0919598 2.5785119 1.8939967 1.0298843
## 85 2.2360953 1.8939967 1.0819491 1.4191561 1.8939967 1.2118306 0.3432948
## 86 0.8733511 3.2638987 2.4236611 2.7715335 3.2638987 2.5785119 1.7164738
## 87 0.3432948 4.1195370 3.2638987 3.6468808 4.1195370 3.4329475 2.5823384
## 88 2.9211347 1.2118306 0.4827728 0.7710528 1.2118306 0.5409745 0.3432948
## 89 4.2926996 0.2440981 1.0892254 0.7641926 0.2440981 0.8771115 1.7164738
## 90 2.7463580 1.4117152 0.7241592 0.8771115 1.4117152 0.7641926 0.2440981
## 91 0.2440981 4.2926996 3.4462515 3.7956317 4.2926996 3.6067636 2.7463580
## 92 3.5730658 0.9763925 0.5409745 1.2156269 0.9763925 0.6865895 1.2069319
## 93 3.2638987 0.8733511 0.3432948 0.4881963 0.8733511 0.2413864 0.6865895
## 94 0.5409745 3.6067636 2.7639228 3.1124753 3.6067636 2.9211347 2.0597685
## 95 3.4462515 0.6865895 0.2440981 0.5446127 0.6865895 0.0000000 0.8733511
## 96 1.2118306 2.9211347 2.0843943 2.4312539 2.9211347 2.2360953 1.3731790
## 97 1.4117152 2.7463580 1.8939967 2.2956598 2.7463580 2.0597685 1.2156269
## 98 2.9211347 1.2118306 0.4827728 0.7710528 1.2118306 0.5409745 0.3432948
## 99 1.5524262 2.5785119 1.7467021 2.0919598 2.5785119 1.8939967 1.0298843
## 100 2.2360953 1.8939967 1.0819491 1.4191561 1.8939967 1.2118306 0.3432948
## 101 3.2677283 0.9959227 0.6865895 0.3432948 0.9959227 0.5409745 0.7710528
## 102 0.6865895 4.8145447 3.9756230 4.2965315 4.8145447 4.1299928 3.2638987
## 103 1.2118306 2.9211347 2.0843943 2.4312539 2.9211347 2.2360953 1.3731790
## 104 2.2360953 1.8939967 1.0819491 1.4191561 1.8939967 1.2118306 0.3432948
## 105 0.8733511 3.2638987 2.4236611 2.7715335 3.2638987 2.5785119 1.7164738
## 106 4.2926996 0.2440981 1.0892254 0.7641926 0.2440981 0.8771115 1.7164738
## 107 0.8733511 3.2638987 2.4236611 2.7715335 3.2638987 2.5785119 1.7164738
## 108 2.5823384 1.6229236 0.9655455 1.0298843 1.6229236 0.9959227 0.3432948
## 109 0.8733511 3.2638987 2.4236611 2.7715335 3.2638987 2.5785119 1.7164738
## 110 0.2413864 4.3162553 3.4934043 3.7762423 4.3162553 3.6354917 2.7639228
## 111 0.2413864 3.9497032 3.1048524 3.4538833 3.9497032 3.2638987 2.4030633
## 112 0.2440981 4.2926996 3.4462515 3.7956317 4.2926996 3.6067636 2.7463580
## 113 0.2413864 3.9497032 3.1048524 3.4538833 3.9497032 3.2638987 2.4030633
## 114 0.6865895 3.4462515 2.6200532 2.9249630 3.4462515 2.7639228 1.8939967
## 115 3.9497032 0.2413864 0.7710528 0.4827728 0.2413864 0.5446127 1.3731790
## 116 1.0892254 3.1575251 2.3818062 2.5785119 3.1575251 2.4918378 1.6229236
## 117 0.2413864 3.9497032 3.1048524 3.4538833 3.9497032 3.2638987 2.4030633
## 118 1.8939967 2.2360953 1.4117152 1.7542231 2.2360953 1.5524262 0.6865895
## 119 1.2156269 5.3219196 4.4721907 4.8221951 5.3219196 4.6357401 3.7762423
## 120 1.5524262 2.5785119 1.7467021 2.0919598 2.5785119 1.8939967 1.0298843
## 121 1.3019294 3.7146725 2.8383121 3.3950498 3.7146725 3.0507831 2.3131585
## 71 72 73 74 75 76 77
## 2
## 3
## 4
## 5
## 6
## 7
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## 9
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## 64
## 65
## 66
## 67
## 68
## 69
## 70
## 71
## 72 0.4881963
## 73 0.5409745 0.8771115
## 74 2.2360953 2.5823384 1.7164738
## 75 0.5409745 0.5409745 1.0819491 2.7639228
## 76 0.3432948 0.7710528 0.2413864 1.8939967 0.8733511
## 77 1.7542231 2.1784507 1.3125041 0.7241592 2.2399190 1.4191561
## 78 0.2440981 0.2440981 0.6865895 2.4030633 0.4827728 0.5446127 1.9626230
## 79 0.6865895 1.0892254 0.2440981 1.5524262 1.2118306 0.3432948 1.0892254
## 80 2.0597685 2.4312539 1.5562377 0.2413864 2.5785119 1.7164738 0.4827728
## 81 3.6067636 3.9535345 3.0896528 1.3731790 4.1299928 3.2638987 1.9515236
## 82 1.3125041 1.7755789 0.9763925 1.2313686 1.7542231 1.0057881 0.5409745
## 83 0.0000000 0.4881963 0.5409745 2.2360953 0.5409745 0.3432948 1.7542231
## 84 1.3731790 1.7542231 0.8771115 0.8733511 1.8939967 1.0298843 0.4881963
## 85 0.6865895 1.0892254 0.2440981 1.5524262 1.2118306 0.3432948 1.0892254
## 86 2.0597685 2.4312539 1.5562377 0.2413864 2.5785119 1.7164738 0.4827728
## 87 2.9249630 3.3073803 2.4312539 0.7710528 3.4329475 2.5823384 1.2118306
## 88 0.0000000 0.4881963 0.5409745 2.2360953 0.5409745 0.3432948 1.7542231
## 89 1.3731790 1.0819491 1.8939967 3.6067636 0.8771115 1.7164738 3.1124753
## 90 0.2413864 0.5446127 0.3432948 2.0597685 0.7641926 0.2440981 1.6338381
## 91 3.0896528 3.4538833 2.5823384 0.8771115 3.6067636 2.7463580 1.4117152
## 92 0.9959227 1.2118306 1.4483183 2.9223195 0.6865895 1.2069319 2.2844497
## 93 0.3432948 0.3432948 0.8733511 2.5785119 0.2413864 0.6865895 2.0919598
## 94 2.4030633 2.7715335 1.8978159 0.2440981 2.9211347 2.0597685 0.7641926
## 95 0.5409745 0.5409745 1.0819491 2.7639228 0.0000000 0.8733511 2.2399190
## 96 1.7164738 2.0919598 1.2156269 0.5409745 2.2360953 1.3731790 0.3432948
## 97 1.5562377 1.9626230 1.0892254 0.7641926 2.0597685 1.2156269 0.2440981
## 98 0.0000000 0.4881963 0.5409745 2.2360953 0.5409745 0.3432948 1.7542231
## 99 1.3731790 1.7542231 0.8771115 0.8733511 1.8939967 1.0298843 0.4881963
## 100 0.6865895 1.0892254 0.2440981 1.5524262 1.2118306 0.3432948 1.0892254
## 101 0.4881963 0.0000000 0.8771115 2.5823384 0.5409745 0.7710528 2.1784507
## 102 3.6067636 3.9535345 3.0896528 1.3731790 4.1299928 3.2638987 1.9515236
## 103 1.7164738 2.0919598 1.2156269 0.5409745 2.2360953 1.3731790 0.3432948
## 104 0.6865895 1.0892254 0.2440981 1.5524262 1.2118306 0.3432948 1.0892254
## 105 2.0597685 2.4312539 1.5562377 0.2413864 2.5785119 1.7164738 0.4827728
## 106 1.3731790 1.0819491 1.8939967 3.6067636 0.8771115 1.7164738 3.1124753
## 107 2.0597685 2.4312539 1.5562377 0.2413864 2.5785119 1.7164738 0.4827728
## 108 0.4827728 0.6865895 0.2440981 1.8978159 0.9959227 0.3432948 1.5421057
## 109 2.0597685 2.4312539 1.5562377 0.2413864 2.5785119 1.7164738 0.4827728
## 110 3.1048524 3.4329475 2.5785119 0.8733511 3.6354917 2.7639228 1.5283853
## 111 2.7463580 3.1124753 2.2399190 0.5446127 3.2638987 2.4030633 1.0819491
## 112 3.0896528 3.4538833 2.5823384 0.8771115 3.6067636 2.7463580 1.4117152
## 113 2.7463580 3.1124753 2.2399190 0.5446127 3.2638987 2.4030633 1.0819491
## 114 2.2360953 2.5823384 1.7164738 0.0000000 2.7639228 1.8939967 0.7241592
## 115 1.0298843 0.7641926 1.5524262 3.2638987 0.5446127 1.3731790 2.7715335
## 116 1.9515236 2.2360953 1.4117152 0.4881963 2.4918378 1.6229236 0.8733511
## 117 2.7463580 3.1124753 2.2399190 0.5446127 3.2638987 2.4030633 1.0819491
## 118 1.0298843 1.4191561 0.5446127 1.2118306 1.5524262 0.6865895 0.7710528
## 119 4.1195370 4.4798379 3.6105942 1.8978159 4.6357401 3.7762423 2.4236611
## 120 1.3731790 1.7542231 0.8771115 0.8733511 1.8939967 1.0298843 0.4881963
## 121 2.6250082 3.0842113 2.2493033 1.2156269 3.0507831 2.3131585 0.9763925
## 78 79 80 81 82 83 84
## 2
## 3
## 4
## 5
## 6
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## 71
## 72
## 73
## 74
## 75
## 76
## 77
## 78
## 79 0.8771115
## 80 2.2399190 1.3731790
## 81 3.7762423 2.9211347 1.5524262
## 82 1.5421057 0.7322944 0.9959227 2.4918378
## 83 0.2440981 0.6865895 2.0597685 3.6067636 1.3125041
## 84 1.5562377 0.6865895 0.6865895 2.2360953 0.5409745 1.3731790
## 85 0.8771115 0.0000000 1.3731790 2.9211347 0.7322944 0.6865895 0.6865895
## 86 2.2399190 1.3731790 0.0000000 1.5524262 0.9959227 2.0597685 0.6865895
## 87 3.1124753 2.2399190 0.8771115 0.7641926 1.7467021 2.9249630 1.5562377
## 88 0.2440981 0.6865895 2.0597685 3.6067636 1.3125041 0.0000000 1.3731790
## 89 1.2118306 2.0597685 3.4329475 4.9788157 2.6313346 1.3731790 2.7463580
## 90 0.3432948 0.5446127 1.8978159 3.4329475 1.2441322 0.2413864 1.2156269
## 91 3.2677283 2.4030633 1.0298843 0.5409745 1.9515236 3.0896528 1.7164738
## 92 1.0819491 1.4687443 2.7048727 4.2351456 1.7467021 0.9959227 2.0652767
## 93 0.2413864 1.0298843 2.4030633 3.9497032 1.6338381 0.3432948 1.7164738
## 94 2.5823384 1.7164738 0.3432948 1.2118306 1.3019294 2.4030633 1.0298843
## 95 0.4827728 1.2118306 2.5785119 4.1299928 1.7542231 0.5409745 1.8939967
## 96 1.8978159 1.0298843 0.3432948 1.8939967 0.7241592 1.7164738 0.3432948
## 97 1.7542231 0.8771115 0.5409745 2.0843943 0.4827728 1.5562377 0.2440981
## 98 0.2440981 0.6865895 2.0597685 3.6067636 1.3125041 0.0000000 1.3731790
## 99 1.5562377 0.6865895 0.6865895 2.2360953 0.5409745 1.3731790 0.0000000
## 100 0.8771115 0.0000000 1.3731790 2.9211347 0.7322944 0.6865895 0.6865895
## 101 0.2440981 1.0892254 2.4312539 3.9535345 1.7755789 0.4881963 1.7542231
## 102 3.7762423 2.9211347 1.5524262 0.0000000 2.4918378 3.6067636 2.2360953
## 103 1.8978159 1.0298843 0.3432948 1.8939967 0.7241592 1.7164738 0.3432948
## 104 0.8771115 0.0000000 1.3731790 2.9211347 0.7322944 0.6865895 0.6865895
## 105 2.2399190 1.3731790 0.0000000 1.5524262 0.9959227 2.0597685 0.6865895
## 106 1.2118306 2.0597685 3.4329475 4.9788157 2.6313346 1.3731790 2.7463580
## 107 2.2399190 1.3731790 0.0000000 1.5524262 0.9959227 2.0597685 0.6865895
## 108 0.5409745 0.4881963 1.7542231 3.2677283 1.2204907 0.4827728 1.0892254
## 109 2.2399190 1.3731790 0.0000000 1.5524262 0.9959227 2.0597685 0.6865895
## 110 3.2638987 2.4236611 1.0819491 0.5446127 2.0652767 3.1048524 1.7467021
## 111 2.9249630 2.0597685 0.6865895 0.8733511 1.6229236 2.7463580 1.3731790
## 112 3.2677283 2.4030633 1.0298843 0.5409745 1.9515236 3.0896528 1.7164738
## 113 2.9249630 2.0597685 0.6865895 0.8733511 1.6229236 2.7463580 1.3731790
## 114 2.4030633 1.5524262 0.2413864 1.3731790 1.2313686 2.2360953 0.8733511
## 115 0.8733511 1.7164738 3.0896528 4.6357401 2.2956598 1.0298843 2.4030633
## 116 2.0843943 1.3019294 0.5446127 1.7542231 1.2313686 1.9515236 0.7241592
## 117 2.9249630 2.0597685 0.6865895 0.8733511 1.6229236 2.7463580 1.3731790
## 118 1.2156269 0.3432948 1.0298843 2.5785119 0.5446127 1.0298843 0.3432948
## 119 4.2965315 3.4329475 2.0597685 0.5446127 2.9574228 4.1195370 2.7463580
## 120 1.5562377 0.6865895 0.6865895 2.2360953 0.5409745 1.3731790 0.0000000
## 121 2.8534067 2.0115762 1.0892254 1.6897047 1.3125041 2.6250082 1.4645888
## 85 86 87 88 89 90 91
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## 86 1.3731790
## 87 2.2399190 0.8771115
## 88 0.6865895 2.0597685 2.9249630
## 89 2.0597685 3.4329475 4.2965315 1.3731790
## 90 0.5446127 1.8978159 2.7715335 0.2413864 1.5524262
## 91 2.4030633 1.0298843 0.2413864 3.0896528 4.4628318 2.9249630
## 92 1.4687443 2.7048727 3.4934043 0.9959227 1.2204907 1.2313686 3.6960192
## 93 1.0298843 2.4030633 3.2677283 0.3432948 1.0298843 0.5409745 3.4329475
## 94 1.7164738 0.3432948 0.5446127 2.4030633 3.7762423 2.2399190 0.6865895
## 95 1.2118306 2.5785119 3.4329475 0.5409745 0.8771115 0.7641926 3.6067636
## 96 1.0298843 0.3432948 1.2156269 1.7164738 3.0896528 1.5562377 1.3731790
## 97 0.8771115 0.5409745 1.3731790 1.5562377 2.9249630 1.4191561 1.5524262
## 98 0.6865895 2.0597685 2.9249630 0.0000000 1.3731790 0.2413864 3.0896528
## 99 0.6865895 0.6865895 1.5562377 1.3731790 2.7463580 1.2156269 1.7164738
## 100 0.0000000 1.3731790 2.2399190 0.6865895 2.0597685 0.5446127 2.4030633
## 101 1.0892254 2.4312539 3.3073803 0.4881963 1.0819491 0.5446127 3.4538833
## 102 2.9211347 1.5524262 0.7641926 3.6067636 4.9788157 3.4329475 0.5409745
## 103 1.0298843 0.3432948 1.2156269 1.7164738 3.0896528 1.5562377 1.3731790
## 104 0.0000000 1.3731790 2.2399190 0.6865895 2.0597685 0.5446127 2.4030633
## 105 1.3731790 0.0000000 0.8771115 2.0597685 3.4329475 1.8978159 1.0298843
## 106 2.0597685 3.4329475 4.2965315 1.3731790 0.0000000 1.5524262 4.4628318
## 107 1.3731790 0.0000000 0.8771115 2.0597685 3.4329475 1.8978159 1.0298843
## 108 0.4881963 1.7542231 2.6313346 0.4827728 1.7467021 0.2413864 2.7715335
## 109 1.3731790 0.0000000 0.8771115 2.0597685 3.4329475 1.8978159 1.0298843
## 110 2.4236611 1.0819491 0.5409745 3.1048524 4.4721907 2.9211347 0.3432948
## 111 2.0597685 0.6865895 0.2440981 2.7463580 4.1195370 2.5823384 0.3432948
## 112 2.4030633 1.0298843 0.2413864 3.0896528 4.4628318 2.9249630 0.0000000
## 113 2.0597685 0.6865895 0.2440981 2.7463580 4.1195370 2.5823384 0.3432948
## 114 1.5524262 0.2413864 0.7710528 2.2360953 3.6067636 2.0597685 0.8771115
## 115 1.7164738 3.0896528 3.9535345 1.0298843 0.3432948 1.2118306 4.1195370
## 116 1.3019294 0.5446127 1.2441322 1.9515236 3.2960163 1.7467021 1.3125041
## 117 2.0597685 0.6865895 0.2440981 2.7463580 4.1195370 2.5823384 0.3432948
## 118 0.3432948 1.0298843 1.8978159 1.0298843 2.4030633 0.8771115 2.0597685
## 119 3.4329475 2.0597685 1.2118306 4.1195370 5.4927160 3.9535345 1.0298843
## 120 0.6865895 0.6865895 1.5562377 1.3731790 2.7463580 1.2156269 1.7164738
## 121 2.0115762 1.0892254 0.9959227 2.6250082 3.9252461 2.5461336 1.2313686
## 92 93 94 95 96 97 98
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## 93 0.8733511
## 94 3.0323875 2.7463580
## 95 0.6865895 0.2413864 2.9211347
## 96 2.3818062 2.0597685 0.6865895 2.2360953
## 97 2.1638981 1.8978159 0.8733511 2.0597685 0.2413864
## 98 0.9959227 0.3432948 2.4030633 0.5409745 1.7164738 1.5562377
## 99 2.0652767 1.7164738 1.0298843 1.8939967 0.3432948 0.2440981 1.3731790
## 100 1.4687443 1.0298843 1.7164738 1.2118306 1.0298843 0.8771115 0.6865895
## 101 1.2118306 0.3432948 2.7715335 0.5409745 2.0919598 1.9626230 0.4881963
## 102 4.2351456 3.9497032 1.2118306 4.1299928 1.8939967 2.0843943 3.6067636
## 103 2.3818062 2.0597685 0.6865895 2.2360953 0.0000000 0.2413864 1.7164738
## 104 1.4687443 1.0298843 1.7164738 1.2118306 1.0298843 0.8771115 0.6865895
## 105 2.7048727 2.4030633 0.3432948 2.5785119 0.3432948 0.5409745 2.0597685
## 106 1.2204907 1.0298843 3.7762423 0.8771115 3.0896528 2.9249630 1.3731790
## 107 2.7048727 2.4030633 0.3432948 2.5785119 0.3432948 0.5409745 2.0597685
## 108 1.4687443 0.7641926 2.0919598 0.9959227 1.4191561 1.3125041 0.4827728
## 109 2.7048727 2.4030633 0.3432948 2.5785119 0.3432948 0.5409745 2.0597685
## 110 3.7868218 3.4462515 0.7641926 3.6354917 1.4117152 1.6229236 3.1048524
## 111 3.3630514 3.0896528 0.3432948 3.2638987 1.0298843 1.2118306 2.7463580
## 112 3.6960192 3.4329475 0.6865895 3.6067636 1.3731790 1.5524262 3.0896528
## 113 3.3630514 3.0896528 0.3432948 3.2638987 1.0298843 1.2118306 2.7463580
## 114 2.9223195 2.5785119 0.2440981 2.7639228 0.5409745 0.7641926 2.2360953
## 115 1.0057881 0.6865895 3.4329475 0.5446127 2.7463580 2.5823384 1.0298843
## 116 2.7543800 2.2844497 0.7322944 2.4918378 0.5409745 0.7641926 1.9515236
## 117 3.3630514 3.0896528 0.3432948 3.2638987 1.0298843 1.2118306 2.7463580
## 118 1.7588171 1.3731790 1.3731790 1.5524262 0.6865895 0.5446127 1.0298843
## 119 4.7038392 4.4628318 1.7164738 4.6357401 2.4030633 2.5785119 4.1195370
## 120 2.0652767 1.7164738 1.0298843 1.8939967 0.3432948 0.2440981 1.3731790
## 121 2.9249630 2.9438642 1.0298843 3.0507831 1.2441322 1.2204907 2.6250082
## 99 100 101 102 103 104 105
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## 100 0.6865895
## 101 1.7542231 1.0892254
## 102 2.2360953 2.9211347 3.9535345
## 103 0.3432948 1.0298843 2.0919598 1.8939967
## 104 0.6865895 0.0000000 1.0892254 2.9211347 1.0298843
## 105 0.6865895 1.3731790 2.4312539 1.5524262 0.3432948 1.3731790
## 106 2.7463580 2.0597685 1.0819491 4.9788157 3.0896528 2.0597685 3.4329475
## 107 0.6865895 1.3731790 2.4312539 1.5524262 0.3432948 1.3731790 0.0000000
## 108 1.0892254 0.4881963 0.6865895 3.2677283 1.4191561 0.4881963 1.7542231
## 109 0.6865895 1.3731790 2.4312539 1.5524262 0.3432948 1.3731790 0.0000000
## 110 1.7467021 2.4236611 3.4329475 0.5446127 1.4117152 2.4236611 1.0819491
## 111 1.3731790 2.0597685 3.1124753 0.8733511 1.0298843 2.0597685 0.6865895
## 112 1.7164738 2.4030633 3.4538833 0.5409745 1.3731790 2.4030633 1.0298843
## 113 1.3731790 2.0597685 3.1124753 0.8733511 1.0298843 2.0597685 0.6865895
## 114 0.8733511 1.5524262 2.5823384 1.3731790 0.5409745 1.5524262 0.2413864
## 115 2.4030633 1.7164738 0.7641926 4.6357401 2.7463580 1.7164738 3.0896528
## 116 0.7241592 1.3019294 2.2360953 1.7542231 0.5409745 1.3019294 0.5446127
## 117 1.3731790 2.0597685 3.1124753 0.8733511 1.0298843 2.0597685 0.6865895
## 118 0.3432948 0.3432948 1.4191561 2.5785119 0.6865895 0.3432948 1.0298843
## 119 2.7463580 3.4329475 4.4798379 0.5446127 2.4030633 3.4329475 2.0597685
## 120 0.0000000 0.6865895 1.7542231 2.2360953 0.3432948 0.6865895 0.6865895
## 121 1.4645888 2.0115762 3.0842113 1.6897047 1.2441322 2.0115762 1.0892254
## 106 107 108 109 110 111 112
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## 107 3.4329475
## 108 1.7467021 1.7542231
## 109 3.4329475 0.0000000 1.7542231
## 110 4.4721907 1.0819491 2.7463580 1.0819491
## 111 4.1195370 0.6865895 2.4312539 0.6865895 0.4827728
## 112 4.4628318 1.0298843 2.7715335 1.0298843 0.3432948 0.3432948
## 113 4.1195370 0.6865895 2.4312539 0.6865895 0.4827728 0.0000000 0.3432948
## 114 3.6067636 0.2413864 1.8978159 0.2413864 0.8733511 0.5446127 0.8771115
## 115 0.3432948 3.0896528 1.4117152 3.0896528 4.1299928 3.7762423 4.1195370
## 116 3.2960163 0.5446127 1.5524262 0.5446127 1.2156269 1.0057881 1.3125041
## 117 4.1195370 0.6865895 2.4312539 0.6865895 0.4827728 0.0000000 0.3432948
## 118 2.4030633 1.0298843 0.7710528 1.0298843 2.0843943 1.7164738 2.0597685
## 119 5.4927160 2.0597685 3.7956317 2.0597685 1.0892254 1.3731790 1.0298843
## 120 2.7463580 0.6865895 1.0892254 0.6865895 1.7467021 1.3731790 1.7164738
## 121 3.9252461 1.0892254 2.4882643 1.0892254 1.5283853 1.0819491 1.2313686
## 113 114 115 116 117 118 119
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## 114 0.5446127
## 115 3.7762423 3.2638987
## 116 1.0057881 0.4881963 2.9574228
## 117 0.0000000 0.5446127 3.7762423 1.0057881
## 118 1.7164738 1.2118306 2.0597685 0.9959227 1.7164738
## 119 1.3731790 1.8978159 5.1494213 2.2956598 1.3731790 3.0896528
## 120 1.3731790 0.8733511 2.4030633 0.7241592 1.3731790 0.3432948 2.7463580
## 121 1.0819491 1.2156269 3.5951051 1.6338381 1.0819491 1.7256530 1.9918455
## 120
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## 121 1.4645888#calculate how many clusters I need
fviz_nbclust(d_scaled, kmeans, method = "wss") + #within sums squares = type of measure identifying what needs to/doesn't need to be merged
labs(subtitle = "Elbow method") 
#when looking at the elbow plot, you're trying to determine the however # of clusters that we need to use (aka the optimal number)
#when looking at degree, you want to look at diminishing returns
#so when slopes are getting closer to zero,is how many clusters you should look at
#choose number of clusters
k <- 4
# Run the cluster analysis
cluster <- kmeans(d_scaled, k)
cluster## K-means clustering with 4 clusters of sizes 27, 26, 29, 39
##
## Cluster means:
## standards discrepancy
## 1 1.2887813 1.3391144
## 2 -0.3138515 -0.2996997
## 3 0.6020021 0.5153795
## 4 -1.1306414 -1.1105104
##
## Clustering vector:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 1 2 4 4 3 4 4 4 2 1 1 2 3 4 1 4 1 2 2 2
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 1 4 2 2 3 2 1 1 3 1 3 2 3 1 1 4 2 3 3 4
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 4 3 4 2 4 3 2 2 3 4 3 3 4 4 1 3 4 2 4 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 4 1 3 4 1 1 1 1 1 3 3 1 3 4 1 3 2 3 3 4
## 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
## 4 2 3 2 3 4 4 3 1 3 4 1 1 4 1 2 2 3 2 3
## 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120
## 1 4 2 3 4 1 4 3 4 4 4 4 4 4 1 2 4 2 4 2
## 121
## 4
##
## Within cluster sum of squares by cluster:
## [1] 5.677955 3.101067 3.135329 13.761864
## (between_SS / total_SS = 89.3 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"#visualize the clustering alogrithim results
library(factoextra)
fviz_cluster(cluster, data = cluster_data, geom = "point", stand = FALSE,
ellipse.type = "t", palette = "jco", ggtheme = theme_minimal())
#OR
plot(cluster_data, col = cluster$cluster)
# count
table(cluster$cluster)##
## 1 2 3 4
## 27 26 29 39K-means clustering was performed on a sample of first-generation professionals (FGPs) based on their scores on the Almost Perfect Scale - Short Form which contains two subscales, standards and discrepancy. Four distinct clusters were identified with different mean scores on these variables. The largest cluster (cluster 4, n = 39) had the lowest mean scores on standards (M = -1.13) and discrepancy (M = -1.11), while the second largest cluster (cluster 1, n = 37) had the highest mean scores on standards (M = 1.29) and discrepancy (M = 1.34). The other two clusters had intermediate mean scores (cluster 3, n = 29, standards M = 0.60, discrepancy M = 0.52; cluster 2, n = 26, standards M = -0.31, discrepancy M = -0.30).
library(dplyr)
library(psych)##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
##
## %+%, alpha# Assign cluster labels to each row in the original data frame
cluster_assignments <- cbind(cluster_data, cluster = cluster$cluster)
cluster_assignments <- cluster_assignments %>% mutate(ID = row_number())
#make a dataframe of just outcome variables
outcome_data <- data.frame(d$anxiety, d$depression, d$swfw, d$wellbeing)
outcome_data <- rename(outcome_data, anxiety = d.anxiety, depression = d.depression, swfw = d.swfw, wellbeing = d.wellbeing)
outcome_data <- outcome_data %>% mutate(ID = row_number())
# Join the cluster assignments with the outcomes_data data frame by participant_id
df_merged <- left_join(cluster_assignments, outcome_data, by = "ID")# Conduct ANOVAs for each outcome variable, comparing the means of each cluster
anova_result_anxiety <- aov(anxiety ~ cluster, data = df_merged)
anova_result_depression <- aov(depression ~ cluster, data = df_merged)
anova_result_workplace_wellbeing <- aov(swfw ~ cluster, data = df_merged)
anova_result_general_wellbeing <- aov(wellbeing ~ cluster, data = df_merged)
anova_result_standards <- aov(standards ~ cluster, data = df_merged)
anova_result_discrepancy <- aov(discrepancy ~ cluster, data = df_merged)
# Conduct Bonferroni-corrected pairwise comparisons between the clusters for each outcome variable
pairwise_anxiety <- pairwise.t.test(df_merged$anxiety, df_merged$cluster, p.adj = "bonferroni")
pairwise_depression <- pairwise.t.test(df_merged$depression, df_merged$cluster, p.adj = "bonferroni")
pairwise_workplace_wellbeing <- pairwise.t.test(df_merged$swfw , df_merged$cluster, p.adj = "bonferroni")
pairwise_general_wellbeing <- pairwise.t.test(df_merged$wellbeing , df_merged$cluster, p.adj = "bonferroni")
pairwise_standards <- pairwise.t.test(df_merged$standards, df_merged$cluster, p.adj = "bonferroni")
pairwise_discrepancy <- pairwise.t.test(df_merged$discrepancy, df_merged$cluster, p.adj = "bonferroni")
print(pairwise_anxiety)##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$anxiety and df_merged$cluster
##
## 1 2 3
## 2 0.0024 - -
## 3 0.2394 0.5941 -
## 4 2.3e-06 0.9871 0.0083
##
## P value adjustment method: bonferroniprint(pairwise_depression)##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$depression and df_merged$cluster
##
## 1 2 3
## 2 0.02187 - -
## 3 0.90866 0.68869 -
## 4 0.00012 1.00000 0.02192
##
## P value adjustment method: bonferroniprint(pairwise_workplace_wellbeing )##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$swfw and df_merged$cluster
##
## 1 2 3
## 2 1 - -
## 3 1 1 -
## 4 1 1 1
##
## P value adjustment method: bonferroniprint(pairwise_general_wellbeing )##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$wellbeing and df_merged$cluster
##
## 1 2 3
## 2 1 - -
## 3 1 1 -
## 4 1 1 1
##
## P value adjustment method: bonferroniprint(pairwise_standards)##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$standards and df_merged$cluster
##
## 1 2 3
## 2 < 2e-16 - -
## 3 8.1e-12 < 2e-16 -
## 4 < 2e-16 < 2e-16 < 2e-16
##
## P value adjustment method: bonferroniprint(pairwise_discrepancy)##
## Pairwise comparisons using t tests with pooled SD
##
## data: df_merged$discrepancy and df_merged$cluster
##
## 1 2 3
## 2 < 2e-16 - -
## 3 1.9e-14 5.0e-14 -
## 4 < 2e-16 2.6e-15 < 2e-16
##
## P value adjustment method: bonferroni# plot a box plot
anxiety_boxplot <- boxplot(anxiety ~ cluster, data = df_merged,
main = "Anxiety by Cluster",
xlab = "Cluster", ylab = "Anxiety")
depression_boxplot <- boxplot(depression ~ cluster, data = df_merged,
main = "Depression by Cluster",
xlab = "Cluster", ylab = "Depression")
swfw_boxplot <- boxplot(swfw ~ cluster, data = df_merged,
main = "Workplace Wellbeing by Cluster",
xlab = "Cluster", ylab = "Workplace Wellbeing")
wellbeing_boxplot <- boxplot(wellbeing ~ cluster, data = df_merged,
main = "Wellbeing by Cluster",
xlab = "Cluster", ylab = "Wellbeing")
standards_boxplot <- boxplot(standards ~ cluster, data = df_merged,
main = "Standards by Cluster",
xlab = "Cluster", ylab = "Standards")
discrepancy_boxplot <- boxplot(discrepancy ~ cluster, data = df_merged,
main = "Discrepancy by Cluster",
xlab = "Cluster", ylab = "Discrepancy")
A one-way analysis of variance (ANOVA) was conducted to determine whether there were significant differences between FGP profiles on the outcome variable: anxiety, depression, workplace wellbeing, and general wellbeing. For the first analysis, the main effect of cluster was significant, F(1, 118) = 20.16, p = 0.0000167, indicating that there were significant differences between FGP profiles on anxiety. For the second analysis, the main effect of cluster was also significant, F(1, 119) = 13.74, p = 0.00032, indicating that there were significant differences between FGP profiles on depression. For the third analysis, the main effect of cluster was not significant, F(1, 117) = 1.158, p = 0.284, indicating that there were no significant differences between FGPs on workplace wellbeing.For the fourth analysis, the main effect of cluster was also not significant, F(1, 119) = 0.146, p = 0.703, indicating that there were no significant differences between FGPs on general wellbeing.
The output shows the pairwise comparisons using t-tests with pooled standard deviations between the variables anxiety, depression, self-worth, well-being, standards, and discrepancy, and the variable cluster. The values in the table are the p-values of the pairwise comparisons between the clusters. The values that are less than the significance level (usually 0.05) indicate that there is a significant difference between the clusters for that particular variable.
For anxiety, the table shows that there is a significant difference between cluster 1 and cluster 2 (p = 0.0024), and between cluster 1 and cluster 4 (p = 0.0000023). However, there is no significant difference between cluster 1 and cluster 3, and between cluster 2 and cluster 3.
For depression, the table shows that there is a significant difference between cluster 1 and cluster 4 (p = 0.00012). However, there is no significant difference between cluster 1 and cluster 2, cluster 1 and cluster 3, and cluster 2 and cluster 3.
For standards and discrepancy, the table shows that there is a significant difference between all the clusters for both variables (p < 0.05).
Overall, the results suggest that there are significant differences between the clusters for most of the variables, except for depression, which only shows a significant difference between cluster 1 and cluster 4.
Linear Regression
# Conducting linear regression analysis
anxiety_lm <- lm(anxiety ~ cluster, data = df_merged)
summary(anxiety_lm)##
## Call:
## lm(formula = anxiety ~ cluster, data = df_merged)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2938 -0.4818 -0.1151 0.4436 2.2054
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.54338 0.16168 15.73 < 2e-16 ***
## cluster -0.24958 0.05559 -4.49 1.67e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6951 on 118 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1459, Adjusted R-squared: 0.1387
## F-statistic: 20.16 on 1 and 118 DF, p-value: 1.672e-05depression_lm <- lm(depression ~ cluster, data = df_merged)
summary(depression_lm)##
## Call:
## lm(formula = depression ~ cluster, data = df_merged)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.1145 -0.4445 -0.1145 0.3697 1.6997
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.30160 0.14626 15.736 < 2e-16 ***
## cluster -0.18709 0.05047 -3.707 0.00032 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6367 on 119 degrees of freedom
## Multiple R-squared: 0.1035, Adjusted R-squared: 0.09597
## F-statistic: 13.74 on 1 and 119 DF, p-value: 0.0003202workplace_wellbeing_lm <- lm(swfw ~ cluster, data = df_merged)
summary(workplace_wellbeing_lm)##
## Call:
## lm(formula = swfw ~ cluster, data = df_merged)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.0967 -0.5374 0.0505 0.6233 1.5762
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.94813 0.19462 25.425 <2e-16 ***
## cluster 0.07284 0.06768 1.076 0.284
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8439 on 117 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.009804, Adjusted R-squared: 0.001341
## F-statistic: 1.158 on 1 and 117 DF, p-value: 0.284general_wellbeing_lm <- lm(wellbeing ~ cluster, data = df_merged)
summary(general_wellbeing_lm)##
## Call:
## lm(formula = wellbeing ~ cluster, data = df_merged)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.05724 -0.60260 -0.02992 0.59740 3.02472
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.94795 0.20698 14.243 <2e-16 ***
## cluster 0.02732 0.07143 0.383 0.703
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.901 on 119 degrees of freedom
## Multiple R-squared: 0.001228, Adjusted R-squared: -0.007165
## F-statistic: 0.1463 on 1 and 119 DF, p-value: 0.7028library(ggplot2)
# Plot for anxiety_lm
p1 <- ggplot(df_merged, aes(x = cluster, y = anxiety)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Anxiety vs Cluster")
# Plot for depression_lm
p2 <- ggplot(df_merged, aes(x = cluster, y = depression)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, color = "blue") +
labs(title = "Depression vs Cluster")
# Plot for workplace_wellbeing_lm
p3 <- ggplot(df_merged, aes(x = cluster, y = swfw)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, color = "green") +
labs(title = "Workplace Wellbeing vs Cluster")
# Plot for general_wellbeing_lm
p4 <- ggplot(df_merged, aes(x = cluster, y = wellbeing)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, color = "purple") +
labs(title = "General Wellbeing vs Cluster")
# Arrange the plots in a 2x2 grid using `patchwork` library
library(patchwork)
p1 + p2 + plot_layout(ncol = 2)## `geom_smooth()` using formula 'y ~ x'## Warning: Removed 1 rows containing non-finite values (stat_smooth).## Warning: Removed 1 rows containing missing values (geom_point).## `geom_smooth()` using formula 'y ~ x'
Linear regression analysis was conducted to investigate the relationship between anxiety, depression, workplace well-being, generall wellbeing, and cluster membership. The results showed a significant negative relationship between anxiety and cluster membership (β = -0.25, t(118) = -4.49, p < 0.001). There was also a significant negative relationship between depression and cluster membership (β = -0.19, t(119) = -3.71, p = 0.0003). However, no significant relationship was found between workplace well-being and cluster membership (β = 0.07, t(117) = 1.08, p = 0.284). There was also no significant relationship between general well-being and cluster membership (β = 0.03, t(119) = 0.38, p = 0.703). The coefficients of determination (R2) indicated that cluster membership accounted for 14.6% and 10.4% of the variance in anxiety and depression scores, respectively. These results suggest that individuals in different clusters may experience different levels of anxiety and depression. However, cluster membership may not be a strong predictor of workplace and general well-being.