Análisis de Componentes Principales (ACP) - Caso Dengue
Lectura de Datos
## city year weekofyear week_start_date ndvi_ne ndvi_nw ndvi_se ndvi_sw
## 1 sj 1990 18 1990-04-30 0.1226000 0.1037250 0.1984833 0.1776167
## 2 sj 1990 19 1990-05-07 0.1699000 0.1421750 0.1623571 0.1554857
## 3 sj 1990 20 1990-05-14 0.0322500 0.1729667 0.1572000 0.1708429
## 4 sj 1990 21 1990-05-21 0.1286333 0.2450667 0.2275571 0.2358857
## 5 sj 1990 22 1990-05-28 0.1962000 0.2622000 0.2512000 0.2473400
## 6 sj 1990 23 1990-06-04 NA 0.1748500 0.2543143 0.1817429
## precipitation_amt_mm reanalysis_air_temp_k reanalysis_avg_temp_k
## 1 12.42 297.5729 297.7429
## 2 22.82 298.2114 298.4429
## 3 34.54 298.7814 298.8786
## 4 15.36 298.9871 299.2286
## 5 7.52 299.5186 299.6643
## 6 9.58 299.6300 299.7643
## reanalysis_dew_point_temp_k reanalysis_max_air_temp_k
## 1 292.4143 299.8
## 2 293.9514 300.9
## 3 295.4343 300.5
## 4 295.3100 301.4
## 5 295.8214 301.9
## 6 295.8514 302.4
## reanalysis_min_air_temp_k reanalysis_precip_amt_kg_per_m2
## 1 295.9 32.00
## 2 296.4 17.94
## 3 297.3 26.10
## 4 297.0 13.90
## 5 297.5 12.20
## 6 298.1 26.49
## reanalysis_relative_humidity_percent reanalysis_sat_precip_amt_mm
## 1 73.36571 12.42
## 2 77.36857 22.82
## 3 82.05286 34.54
## 4 80.33714 15.36
## 5 80.46000 7.52
## 6 79.89143 9.58
## reanalysis_specific_humidity_g_per_kg reanalysis_tdtr_k station_avg_temp_c
## 1 14.01286 2.628571 25.44286
## 2 15.37286 2.371429 26.71429
## 3 16.84857 2.300000 26.71429
## 4 16.67286 2.428571 27.47143
## 5 17.21000 3.014286 28.94286
## 6 17.21286 2.100000 28.11429
## station_diur_temp_rng_c station_max_temp_c station_min_temp_c
## 1 6.900000 29.4 20.0
## 2 6.371429 31.7 22.2
## 3 6.485714 32.2 22.8
## 4 6.771429 33.3 23.3
## 5 9.371429 35.0 23.9
## 6 6.942857 34.4 23.9
## station_precip_mm
## 1 16.0
## 2 8.6
## 3 41.4
## 4 4.0
## 5 5.8
## 6 39.1## 'data.frame': 1456 obs. of 24 variables:
## $ city : chr "sj" "sj" "sj" "sj" ...
## $ year : int 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ...
## $ weekofyear : int 18 19 20 21 22 23 24 25 26 27 ...
## $ week_start_date : chr "1990-04-30" "1990-05-07" "1990-05-14" "1990-05-21" ...
## $ ndvi_ne : num 0.1226 0.1699 0.0323 0.1286 0.1962 ...
## $ ndvi_nw : num 0.104 0.142 0.173 0.245 0.262 ...
## $ ndvi_se : num 0.198 0.162 0.157 0.228 0.251 ...
## $ ndvi_sw : num 0.178 0.155 0.171 0.236 0.247 ...
## $ precipitation_amt_mm : num 12.42 22.82 34.54 15.36 7.52 ...
## $ reanalysis_air_temp_k : num 298 298 299 299 300 ...
## $ reanalysis_avg_temp_k : num 298 298 299 299 300 ...
## $ reanalysis_dew_point_temp_k : num 292 294 295 295 296 ...
## $ reanalysis_max_air_temp_k : num 300 301 300 301 302 ...
## $ reanalysis_min_air_temp_k : num 296 296 297 297 298 ...
## $ reanalysis_precip_amt_kg_per_m2 : num 32 17.9 26.1 13.9 12.2 ...
## $ reanalysis_relative_humidity_percent : num 73.4 77.4 82.1 80.3 80.5 ...
## $ reanalysis_sat_precip_amt_mm : num 12.42 22.82 34.54 15.36 7.52 ...
## $ reanalysis_specific_humidity_g_per_kg: num 14 15.4 16.8 16.7 17.2 ...
## $ reanalysis_tdtr_k : num 2.63 2.37 2.3 2.43 3.01 ...
## $ station_avg_temp_c : num 25.4 26.7 26.7 27.5 28.9 ...
## $ station_diur_temp_rng_c : num 6.9 6.37 6.49 6.77 9.37 ...
## $ station_max_temp_c : num 29.4 31.7 32.2 33.3 35 34.4 32.2 33.9 33.9 33.9 ...
## $ station_min_temp_c : num 20 22.2 22.8 23.3 23.9 23.9 23.3 22.8 22.8 24.4 ...
## $ station_precip_mm : num 16 8.6 41.4 4 5.8 39.1 29.7 21.1 21.1 1.1 ...Limpienza
Filtrar datos del año 2000 al 2010
## city year weekofyear week_start_date ndvi_ne ndvi_nw ndvi_se
## 504 sj 2000 52 2000-01-01 -0.13360 -0.061225 0.1682000
## 505 sj 2000 1 2000-01-08 0.20635 0.161300 0.1398833
## 506 sj 2000 2 2000-01-15 0.33700 0.307850 0.2466857
## 507 sj 2000 3 2000-01-22 0.35300 0.307300 0.3262714
## 508 sj 2000 4 2000-01-29 0.34190 0.228000 0.3297500
## 509 sj 2000 5 2000-02-05 0.29455 0.223900 0.2389333
## ndvi_sw precipitation_amt_mm reanalysis_air_temp_k reanalysis_avg_temp_k
## 504 0.08631111 40.35 298.3671 298.3071
## 505 0.09583333 81.73 298.1486 298.1643
## 506 0.16862860 45.19 297.4414 297.5857
## 507 0.29142860 0.00 296.5886 296.4786
## 508 0.38142000 0.00 296.1843 296.3643
## 509 0.16070000 0.00 297.6714 297.8643
## reanalysis_dew_point_temp_k reanalysis_max_air_temp_k
## 504 293.8871 300.3
## 505 294.3557 299.9
## 506 293.1914 299.1
## 507 290.8529 299.0
## 508 289.8271 299.0
## 509 292.7343 299.8
## reanalysis_min_air_temp_k reanalysis_precip_amt_kg_per_m2
## 504 296.4 12.34
## 505 296.5 32.30
## 506 296.1 47.10
## 507 293.2 14.70
## 508 292.6 0.70
## 509 295.8 2.02
## reanalysis_relative_humidity_percent reanalysis_sat_precip_amt_mm
## 504 76.31714 40.35
## 505 79.60714 81.73
## 506 77.34286 45.19
## 507 70.45714 0.00
## 508 67.76571 0.00
## 509 74.06286 0.00
## reanalysis_specific_humidity_g_per_kg reanalysis_tdtr_k station_avg_temp_c
## 504 15.25714 2.642857 25.47143
## 505 15.72286 1.900000 25.12857
## 506 14.61286 2.057143 25.11429
## 507 12.61000 1.842857 23.61429
## 508 11.96429 3.100000 22.84286
## 509 14.21286 2.242857 25.17143
## station_diur_temp_rng_c station_max_temp_c station_min_temp_c
## 504 6.557143 29.4 21.1
## 505 5.314286 29.4 21.7
## 506 5.157143 28.3 21.7
## 507 4.828571 27.2 20.0
## 508 6.842857 28.3 17.8
## 509 7.442857 30.0 20.6
## station_precip_mm
## 504 7.9
## 505 28.6
## 506 12.0
## 507 17.7
## 508 2.0
## 509 14.1omitiendo los valores NA sin perder valores
caso_dengue_Filtrado<- caso_dengue_Filtrado[!is.na(caso_dengue_Filtrado$ndvi_ne)& !is.na(caso_dengue_Filtrado$ndvi_nw)& !is.na(caso_dengue_Filtrado$ndvi_se)& !is.na(caso_dengue_Filtrado$ndvi_sw)& !is.na(caso_dengue_Filtrado$precipitation_amt_mm)& !is.na(caso_dengue_Filtrado$reanalysis_air_temp_k)& !is.na(caso_dengue_Filtrado$reanalysis_avg_temp_k)& !is.na(caso_dengue_Filtrado$reanalysis_dew_point_temp_k)& !is.na(caso_dengue_Filtrado$reanalysis_max_air_temp_k)& !is.na(caso_dengue_Filtrado$reanalysis_min_air_temp_k)& !is.na(caso_dengue_Filtrado$reanalysis_precip_amt_kg_per_m2)& !is.na(caso_dengue_Filtrado$reanalysis_relative_humidity_percent)& !is.na(caso_dengue_Filtrado$reanalysis_sat_precip_amt_mm)& !is.na(caso_dengue_Filtrado$reanalysis_specific_humidity_g_per_kg)& !is.na(caso_dengue_Filtrado$reanalysis_tdtr_k)& !is.na(caso_dengue_Filtrado$station_avg_temp_c)& !is.na(caso_dengue_Filtrado$station_diur_temp_rng_c)& !is.na(caso_dengue_Filtrado$station_max_temp_c)& !is.na(caso_dengue_Filtrado$station_min_temp_c)& !is.na(caso_dengue_Filtrado$station_precip_mm),] 1.2 Determinante de la matriz de correlación
# Seleccionar solo las columnas numéricas
data_numerica <- caso_dengue_Filtrado[, c("weekofyear", "ndvi_ne", "ndvi_nw", "ndvi_se", "ndvi_sw",
"precipitation_amt_mm", "reanalysis_air_temp_k", "reanalysis_avg_temp_k",
"reanalysis_dew_point_temp_k", "reanalysis_max_air_temp_k",
"reanalysis_min_air_temp_k", "reanalysis_precip_amt_kg_per_m2",
"reanalysis_relative_humidity_percent", "reanalysis_specific_humidity_g_per_kg",
"reanalysis_tdtr_k", "station_avg_temp_c", "station_diur_temp_rng_c",
"station_max_temp_c", "station_min_temp_c")]
r<-cor(data_numerica)
r## weekofyear ndvi_ne ndvi_nw
## weekofyear 1.00000000 0.06478131 0.05581637
## ndvi_ne 0.06478131 1.00000000 0.87217315
## ndvi_nw 0.05581637 0.87217315 1.00000000
## ndvi_se 0.17209509 0.62280399 0.58489103
## ndvi_sw 0.10704370 0.68472143 0.68083102
## precipitation_amt_mm 0.05322598 0.23671772 0.23897118
## reanalysis_air_temp_k 0.37120694 -0.38186468 -0.37088306
## reanalysis_avg_temp_k 0.43138407 -0.07890628 -0.06647044
## reanalysis_dew_point_temp_k 0.22534406 0.06999570 0.09658310
## reanalysis_max_air_temp_k 0.27566328 0.65205603 0.65054121
## reanalysis_min_air_temp_k 0.10560221 -0.64724471 -0.63143196
## reanalysis_precip_amt_kg_per_m2 -0.03705542 0.25025717 0.25331715
## reanalysis_relative_humidity_percent -0.09882910 0.47668844 0.49037067
## reanalysis_specific_humidity_g_per_kg 0.22816207 0.11199252 0.13799024
## reanalysis_tdtr_k 0.14961383 0.69432035 0.68895059
## station_avg_temp_c 0.28787039 0.22846383 0.24661517
## station_diur_temp_rng_c 0.09141036 0.67119821 0.68553424
## station_max_temp_c 0.21656092 0.53851364 0.55317317
## station_min_temp_c 0.16373209 -0.33930107 -0.34974193
## ndvi_se ndvi_sw
## weekofyear 0.172095087 0.107043697
## ndvi_ne 0.622803992 0.684721429
## ndvi_nw 0.584891030 0.680831023
## ndvi_se 1.000000000 0.799734672
## ndvi_sw 0.799734672 1.000000000
## precipitation_amt_mm 0.057466796 0.111455671
## reanalysis_air_temp_k -0.159173709 -0.236781175
## reanalysis_avg_temp_k 0.033926251 -0.002058904
## reanalysis_dew_point_temp_k -0.005437048 0.021226899
## reanalysis_max_air_temp_k 0.440735694 0.524734231
## reanalysis_min_air_temp_k -0.381126725 -0.471620833
## reanalysis_precip_amt_kg_per_m2 0.051501611 0.136447170
## reanalysis_relative_humidity_percent 0.186743453 0.289662347
## reanalysis_specific_humidity_g_per_kg 0.019967516 0.054000689
## reanalysis_tdtr_k 0.454214787 0.540555425
## station_avg_temp_c 0.126054262 0.160510966
## station_diur_temp_rng_c 0.433169219 0.532916677
## station_max_temp_c 0.312649606 0.410001818
## station_min_temp_c -0.249143373 -0.302376835
## precipitation_amt_mm
## weekofyear 0.0532259774
## ndvi_ne 0.2367177188
## ndvi_nw 0.2389711810
## ndvi_se 0.0574667959
## ndvi_sw 0.1114556709
## precipitation_amt_mm 1.0000000000
## reanalysis_air_temp_k -0.1242114968
## reanalysis_avg_temp_k -0.0001383778
## reanalysis_dew_point_temp_k 0.4064927775
## reanalysis_max_air_temp_k 0.2374141935
## reanalysis_min_air_temp_k -0.1560839204
## reanalysis_precip_amt_kg_per_m2 0.4634993443
## reanalysis_relative_humidity_percent 0.4903264138
## reanalysis_specific_humidity_g_per_kg 0.4220773618
## reanalysis_tdtr_k 0.1835888119
## station_avg_temp_c 0.2038489681
## station_diur_temp_rng_c 0.1943907079
## station_max_temp_c 0.2927646655
## station_min_temp_c 0.0458405970
## reanalysis_air_temp_k
## weekofyear 0.37120694
## ndvi_ne -0.38186468
## ndvi_nw -0.37088306
## ndvi_se -0.15917371
## ndvi_sw -0.23678117
## precipitation_amt_mm -0.12421150
## reanalysis_air_temp_k 1.00000000
## reanalysis_avg_temp_k 0.89987117
## reanalysis_dew_point_temp_k 0.37650493
## reanalysis_max_air_temp_k -0.03897166
## reanalysis_min_air_temp_k 0.73373153
## reanalysis_precip_amt_kg_per_m2 -0.23085068
## reanalysis_relative_humidity_percent -0.54922674
## reanalysis_specific_humidity_g_per_kg 0.35384225
## reanalysis_tdtr_k -0.27611231
## station_avg_temp_c 0.50063198
## station_diur_temp_rng_c -0.26678531
## station_max_temp_c 0.10800775
## station_min_temp_c 0.65355398
## reanalysis_avg_temp_k
## weekofyear 0.4313840661
## ndvi_ne -0.0789062837
## ndvi_nw -0.0664704410
## ndvi_se 0.0339262509
## ndvi_sw -0.0020589037
## precipitation_amt_mm -0.0001383778
## reanalysis_air_temp_k 0.8998711731
## reanalysis_avg_temp_k 1.0000000000
## reanalysis_dew_point_temp_k 0.4695954826
## reanalysis_max_air_temp_k 0.3561808298
## reanalysis_min_air_temp_k 0.4508699797
## reanalysis_precip_amt_kg_per_m2 -0.1137332038
## reanalysis_relative_humidity_percent -0.3328222867
## reanalysis_specific_humidity_g_per_kg 0.4668836085
## reanalysis_tdtr_k 0.1201167347
## station_avg_temp_c 0.6666570639
## station_diur_temp_rng_c 0.0992915376
## station_max_temp_c 0.4208532206
## station_min_temp_c 0.5099157380
## reanalysis_dew_point_temp_k
## weekofyear 0.225344056
## ndvi_ne 0.069995700
## ndvi_nw 0.096583102
## ndvi_se -0.005437048
## ndvi_sw 0.021226899
## precipitation_amt_mm 0.406492778
## reanalysis_air_temp_k 0.376504935
## reanalysis_avg_temp_k 0.469595483
## reanalysis_dew_point_temp_k 1.000000000
## reanalysis_max_air_temp_k 0.175987257
## reanalysis_min_air_temp_k 0.329963317
## reanalysis_precip_amt_kg_per_m2 0.469250446
## reanalysis_relative_humidity_percent 0.557371605
## reanalysis_specific_humidity_g_per_kg 0.996657369
## reanalysis_tdtr_k -0.073768892
## station_avg_temp_c 0.647861409
## station_diur_temp_rng_c 0.035365854
## station_max_temp_c 0.413675255
## station_min_temp_c 0.579551117
## reanalysis_max_air_temp_k
## weekofyear 0.27566328
## ndvi_ne 0.65205603
## ndvi_nw 0.65054121
## ndvi_se 0.44073569
## ndvi_sw 0.52473423
## precipitation_amt_mm 0.23741419
## reanalysis_air_temp_k -0.03897166
## reanalysis_avg_temp_k 0.35618083
## reanalysis_dew_point_temp_k 0.17598726
## reanalysis_max_air_temp_k 1.00000000
## reanalysis_min_air_temp_k -0.60803726
## reanalysis_precip_amt_kg_per_m2 0.19777548
## reanalysis_relative_humidity_percent 0.30704266
## reanalysis_specific_humidity_g_per_kg 0.22022469
## reanalysis_tdtr_k 0.91820745
## station_avg_temp_c 0.49119845
## station_diur_temp_rng_c 0.84934908
## station_max_temp_c 0.80729802
## station_min_temp_c -0.26167316
## reanalysis_min_air_temp_k
## weekofyear 0.1056022
## ndvi_ne -0.6472447
## ndvi_nw -0.6314320
## ndvi_se -0.3811267
## ndvi_sw -0.4716208
## precipitation_amt_mm -0.1560839
## reanalysis_air_temp_k 0.7337315
## reanalysis_avg_temp_k 0.4508700
## reanalysis_dew_point_temp_k 0.3299633
## reanalysis_max_air_temp_k -0.6080373
## reanalysis_min_air_temp_k 1.0000000
## reanalysis_precip_amt_kg_per_m2 -0.1516834
## reanalysis_relative_humidity_percent -0.4305611
## reanalysis_specific_humidity_g_per_kg 0.2850367
## reanalysis_tdtr_k -0.8033180
## station_avg_temp_c 0.1151225
## station_diur_temp_rng_c -0.7046676
## station_max_temp_c -0.3715143
## station_min_temp_c 0.7075609
## reanalysis_precip_amt_kg_per_m2
## weekofyear -0.037055422
## ndvi_ne 0.250257167
## ndvi_nw 0.253317152
## ndvi_se 0.051501611
## ndvi_sw 0.136447170
## precipitation_amt_mm 0.463499344
## reanalysis_air_temp_k -0.230850677
## reanalysis_avg_temp_k -0.113733204
## reanalysis_dew_point_temp_k 0.469250446
## reanalysis_max_air_temp_k 0.197775477
## reanalysis_min_air_temp_k -0.151683369
## reanalysis_precip_amt_kg_per_m2 1.000000000
## reanalysis_relative_humidity_percent 0.637146150
## reanalysis_specific_humidity_g_per_kg 0.493222983
## reanalysis_tdtr_k 0.098628365
## station_avg_temp_c 0.136034173
## station_diur_temp_rng_c 0.192332257
## station_max_temp_c 0.229150948
## station_min_temp_c -0.003709587
## reanalysis_relative_humidity_percent
## weekofyear -0.09882910
## ndvi_ne 0.47668844
## ndvi_nw 0.49037067
## ndvi_se 0.18674345
## ndvi_sw 0.28966235
## precipitation_amt_mm 0.49032641
## reanalysis_air_temp_k -0.54922674
## reanalysis_avg_temp_k -0.33282229
## reanalysis_dew_point_temp_k 0.55737160
## reanalysis_max_air_temp_k 0.30704266
## reanalysis_min_air_temp_k -0.43056112
## reanalysis_precip_amt_kg_per_m2 0.63714615
## reanalysis_relative_humidity_percent 1.00000000
## reanalysis_specific_humidity_g_per_kg 0.58103349
## reanalysis_tdtr_k 0.29277170
## station_avg_temp_c 0.18958189
## station_diur_temp_rng_c 0.37332840
## station_max_temp_c 0.36655581
## station_min_temp_c -0.09980724
## reanalysis_specific_humidity_g_per_kg
## weekofyear 0.22816207
## ndvi_ne 0.11199252
## ndvi_nw 0.13799024
## ndvi_se 0.01996752
## ndvi_sw 0.05400069
## precipitation_amt_mm 0.42207736
## reanalysis_air_temp_k 0.35384225
## reanalysis_avg_temp_k 0.46688361
## reanalysis_dew_point_temp_k 0.99665737
## reanalysis_max_air_temp_k 0.22022469
## reanalysis_min_air_temp_k 0.28503674
## reanalysis_precip_amt_kg_per_m2 0.49322298
## reanalysis_relative_humidity_percent 0.58103349
## reanalysis_specific_humidity_g_per_kg 1.00000000
## reanalysis_tdtr_k -0.02602583
## station_avg_temp_c 0.65725022
## station_diur_temp_rng_c 0.08147201
## station_max_temp_c 0.44768660
## station_min_temp_c 0.54911591
## reanalysis_tdtr_k station_avg_temp_c
## weekofyear 0.14961383 0.2878704
## ndvi_ne 0.69432035 0.2284638
## ndvi_nw 0.68895059 0.2466152
## ndvi_se 0.45421479 0.1260543
## ndvi_sw 0.54055542 0.1605110
## precipitation_amt_mm 0.18358881 0.2038490
## reanalysis_air_temp_k -0.27611231 0.5006320
## reanalysis_avg_temp_k 0.12011673 0.6666571
## reanalysis_dew_point_temp_k -0.07376889 0.6478614
## reanalysis_max_air_temp_k 0.91820745 0.4911984
## reanalysis_min_air_temp_k -0.80331800 0.1151225
## reanalysis_precip_amt_kg_per_m2 0.09862836 0.1360342
## reanalysis_relative_humidity_percent 0.29277170 0.1895819
## reanalysis_specific_humidity_g_per_kg -0.02602583 0.6572502
## reanalysis_tdtr_k 1.00000000 0.2847040
## station_avg_temp_c 0.28470404 1.0000000
## station_diur_temp_rng_c 0.87845245 0.3980749
## station_max_temp_c 0.68392524 0.7441571
## station_min_temp_c -0.47821019 0.5100394
## station_diur_temp_rng_c
## weekofyear 0.09141036
## ndvi_ne 0.67119821
## ndvi_nw 0.68553424
## ndvi_se 0.43316922
## ndvi_sw 0.53291668
## precipitation_amt_mm 0.19439071
## reanalysis_air_temp_k -0.26678531
## reanalysis_avg_temp_k 0.09929154
## reanalysis_dew_point_temp_k 0.03536585
## reanalysis_max_air_temp_k 0.84934908
## reanalysis_min_air_temp_k -0.70466760
## reanalysis_precip_amt_kg_per_m2 0.19233226
## reanalysis_relative_humidity_percent 0.37332840
## reanalysis_specific_humidity_g_per_kg 0.08147201
## reanalysis_tdtr_k 0.87845245
## station_avg_temp_c 0.39807485
## station_diur_temp_rng_c 1.00000000
## station_max_temp_c 0.77766688
## station_min_temp_c -0.46621311
## station_max_temp_c station_min_temp_c
## weekofyear 0.216560915 0.163732088
## ndvi_ne 0.538513636 -0.339301068
## ndvi_nw 0.553173168 -0.349741930
## ndvi_se 0.312649606 -0.249143373
## ndvi_sw 0.410001818 -0.302376835
## precipitation_amt_mm 0.292764666 0.045840597
## reanalysis_air_temp_k 0.108007746 0.653553982
## reanalysis_avg_temp_k 0.420853221 0.509915738
## reanalysis_dew_point_temp_k 0.413675255 0.579551117
## reanalysis_max_air_temp_k 0.807298023 -0.261673160
## reanalysis_min_air_temp_k -0.371514304 0.707560936
## reanalysis_precip_amt_kg_per_m2 0.229150948 -0.003709587
## reanalysis_relative_humidity_percent 0.366555809 -0.099807236
## reanalysis_specific_humidity_g_per_kg 0.447686604 0.549115912
## reanalysis_tdtr_k 0.683925239 -0.478210193
## station_avg_temp_c 0.744157127 0.510039361
## station_diur_temp_rng_c 0.777666879 -0.466213114
## station_max_temp_c 1.000000000 0.001838239
## station_min_temp_c 0.001838239 1.000000000## [1] 4.396731e-15Es valor que estan cercno de cero , no indica que existe una alta correlacion entera las variables.
1.3 Índice KMO
## [1] 0.838706El KMO es relevante y apropiado para evaluar la idoneidad de tus datos para el ACP, y un valor de 0.838706 sugiere que las variables tienen una adecuación razonablemente alta para esta técnica.
1.4 Prueba de esfericidad de Bartlett
## $chisq
## [1] 3035.819
##
## $p.value
## [1] 0
##
## $df
## [1] 171## [1] 32.67057la prueba de Bartlett devuelve un estadístico de chi-cuadrado de 3035.819 y un valor p muy cercano a cero (0), lo que indica que hay suficiente evidencia para rechazar la hipótesis nula. Esto sugiere que las variables están correlacionadas entre sí y, por lo tanto, son adecuadas para el análisis de componentes principales.
El valor de chi-cuadrado crítico para un nivel de significancia de 0.05 y 171 grados de libertad (el número total de elementos únicos en la matriz de correlación) es 3035.819, que es mayor que el estadístico de chi-cuadrado obtenido. Esto confirma la significancia estadística de la prueba y respalda aún más la conclusión de que las variables están correlacionadas entre sí.
En resumen, los resultados sugieren que las variables son adecuadas para realizar un análisis de componentes principales, ya que están correlacionadas entre sí.
1.5 Índices MSA
## weekofyear ndvi_ne
## 0.8910407 0.9133581
## ndvi_nw ndvi_se
## 0.9159085 0.8285952
## ndvi_sw precipitation_amt_mm
## 0.8719707 0.9380781
## reanalysis_air_temp_k reanalysis_avg_temp_k
## 0.7159548 0.7813980
## reanalysis_dew_point_temp_k reanalysis_max_air_temp_k
## 0.7475487 0.9228032
## reanalysis_min_air_temp_k reanalysis_precip_amt_kg_per_m2
## 0.8531474 0.8332946
## reanalysis_relative_humidity_percent reanalysis_specific_humidity_g_per_kg
## 0.6852452 0.8376099
## reanalysis_tdtr_k station_avg_temp_c
## 0.8162317 0.8306627
## station_diur_temp_rng_c station_max_temp_c
## 0.8791700 0.9154006
## station_min_temp_c
## 0.8259358Estos valores indican que la mayoría de las variables tienen una adecuación bastante alta para el análisis factorial, ya que están cercanas a 1. Esto sugiere que estas variables podrían ser apropiadas para usar en un análisis factorial, como el Análisis de Componentes Principales (PCA), si ese es tu objetivo.
2. Obtención de los Componentes
## weekofyear ndvi_ne ndvi_nw
## weekofyear 227.3240533 0.148671376 0.111648045
## ndvi_ne 0.1486714 0.023169142 0.017612642
## ndvi_nw 0.1116480 0.017612642 0.017600849
## ndvi_se 0.2035352 0.007436263 0.006086816
## ndvi_sw 0.1477785 0.009543250 0.008270535
## precipitation_amt_mm 34.9531677 1.569372143 1.380869205
## reanalysis_air_temp_k 8.0349936 -0.083447092 -0.070639980
## reanalysis_avg_temp_k 8.5572559 -0.015802081 -0.011602274
## reanalysis_dew_point_temp_k 5.0411135 0.015808258 0.019011905
## reanalysis_max_air_temp_k 13.9816537 0.333884932 0.290334442
## reanalysis_min_air_temp_k 4.3113504 -0.266772528 -0.226835485
## reanalysis_precip_amt_kg_per_m2 -25.5226433 1.740174033 1.535262346
## reanalysis_relative_humidity_percent -12.1694428 0.592587870 0.531317917
## reanalysis_specific_humidity_g_per_kg 5.1931328 0.025733999 0.027636208
## reanalysis_tdtr_k 8.3204076 0.389820831 0.337135949
## station_avg_temp_c 5.2999915 0.042464684 0.039952327
## station_diur_temp_rng_c 3.2216583 0.238818037 0.212597096
## station_max_temp_c 6.5688210 0.164905951 0.147642902
## station_min_temp_c 3.7357298 -0.078155430 -0.070215578
## ndvi_se ndvi_sw
## weekofyear 0.203535204 0.147778491
## ndvi_ne 0.007436263 0.009543250
## ndvi_nw 0.006086816 0.008270535
## ndvi_se 0.006153139 0.005744096
## ndvi_sw 0.005744096 0.008384069
## precipitation_amt_mm 0.196338538 0.444497989
## reanalysis_air_temp_k -0.017925301 -0.031125859
## reanalysis_avg_temp_k 0.003501321 -0.000248034
## reanalysis_dew_point_temp_k -0.000632804 0.002883843
## reanalysis_max_air_temp_k 0.116301020 0.161630664
## reanalysis_min_air_temp_k -0.080953456 -0.116933253
## reanalysis_precip_amt_kg_per_m2 0.184552686 0.570746358
## reanalysis_relative_humidity_percent 0.119634632 0.216612064
## reanalysis_specific_humidity_g_per_kg 0.002364480 0.007464316
## reanalysis_tdtr_k 0.131419500 0.182565132
## station_avg_temp_c 0.012074284 0.017946824
## station_diur_temp_rng_c 0.079426846 0.114063870
## station_max_temp_c 0.049339064 0.075526240
## station_min_temp_c -0.029574449 -0.041898156
## precipitation_amt_mm
## weekofyear 3.495317e+01
## ndvi_ne 1.569372e+00
## ndvi_nw 1.380869e+00
## ndvi_se 1.963385e-01
## ndvi_sw 4.444980e-01
## precipitation_amt_mm 1.897057e+03
## reanalysis_air_temp_k -7.766918e+00
## reanalysis_avg_temp_k -7.929656e-03
## reanalysis_dew_point_temp_k 2.626943e+01
## reanalysis_max_air_temp_k 3.478595e+01
## reanalysis_min_air_temp_k -1.840840e+01
## reanalysis_precip_amt_kg_per_m2 9.222327e+02
## reanalysis_relative_humidity_percent 1.744169e+02
## reanalysis_specific_humidity_g_per_kg 2.775208e+01
## reanalysis_tdtr_k 2.949420e+01
## station_avg_temp_c 1.084187e+01
## station_diur_temp_rng_c 1.979142e+01
## station_max_temp_c 2.565332e+01
## station_min_temp_c 3.021408e+00
## reanalysis_air_temp_k
## weekofyear 8.03499357
## ndvi_ne -0.08344709
## ndvi_nw -0.07063998
## ndvi_se -0.01792530
## ndvi_sw -0.03112586
## precipitation_amt_mm -7.76691845
## reanalysis_air_temp_k 2.06107360
## reanalysis_avg_temp_k 1.69970995
## reanalysis_dew_point_temp_k 0.80200134
## reanalysis_max_air_temp_k -0.18821427
## reanalysis_min_air_temp_k 2.85234170
## reanalysis_precip_amt_kg_per_m2 -15.14011211
## reanalysis_relative_humidity_percent -6.43963999
## reanalysis_specific_humidity_g_per_kg 0.76686640
## reanalysis_tdtr_k -1.46211892
## station_avg_temp_c 0.87764889
## station_diur_temp_rng_c -0.89530297
## station_max_temp_c 0.31195094
## station_min_temp_c 1.41986539
## reanalysis_avg_temp_k
## weekofyear 8.557255938
## ndvi_ne -0.015802081
## ndvi_nw -0.011602274
## ndvi_se 0.003501321
## ndvi_sw -0.000248034
## precipitation_amt_mm -0.007929656
## reanalysis_air_temp_k 1.699709947
## reanalysis_avg_temp_k 1.730993562
## reanalysis_dew_point_temp_k 0.916704381
## reanalysis_max_air_temp_k 1.576431840
## reanalysis_min_air_temp_k 1.606263038
## reanalysis_precip_amt_kg_per_m2 -6.835750245
## reanalysis_relative_humidity_percent -3.576212282
## reanalysis_specific_humidity_g_per_kg 0.927298651
## reanalysis_tdtr_k 0.582909882
## station_avg_temp_c 1.071039984
## station_diur_temp_rng_c 0.305366451
## station_max_temp_c 1.113943164
## station_min_temp_c 1.015231537
## reanalysis_dew_point_temp_k
## weekofyear 5.041113467
## ndvi_ne 0.015808258
## ndvi_nw 0.019011905
## ndvi_se -0.000632804
## ndvi_sw 0.002883843
## precipitation_amt_mm 26.269433273
## reanalysis_air_temp_k 0.802001339
## reanalysis_avg_temp_k 0.916704381
## reanalysis_dew_point_temp_k 2.201483021
## reanalysis_max_air_temp_k 0.878407068
## reanalysis_min_air_temp_k 1.325686857
## reanalysis_precip_amt_kg_per_m2 31.806329364
## reanalysis_relative_humidity_percent 6.754071816
## reanalysis_specific_humidity_g_per_kg 2.232373339
## reanalysis_tdtr_k -0.403720780
## station_avg_temp_c 1.173803106
## station_diur_temp_rng_c 0.122660063
## station_max_temp_c 1.234814909
## station_min_temp_c 1.301272869
## reanalysis_max_air_temp_k
## weekofyear 13.9816537
## ndvi_ne 0.3338849
## ndvi_nw 0.2903344
## ndvi_se 0.1163010
## ndvi_sw 0.1616307
## precipitation_amt_mm 34.7859453
## reanalysis_air_temp_k -0.1882143
## reanalysis_avg_temp_k 1.5764318
## reanalysis_dew_point_temp_k 0.8784071
## reanalysis_max_air_temp_k 11.3165452
## reanalysis_min_air_temp_k -5.5386605
## reanalysis_precip_amt_kg_per_m2 30.3934891
## reanalysis_relative_humidity_percent 8.4356552
## reanalysis_specific_humidity_g_per_kg 1.1183718
## reanalysis_tdtr_k 11.3932576
## station_avg_temp_c 2.0177594
## station_diur_temp_rng_c 6.6788934
## station_max_temp_c 5.4635569
## station_min_temp_c -1.3320946
## reanalysis_min_air_temp_k
## weekofyear 4.31135038
## ndvi_ne -0.26677253
## ndvi_nw -0.22683548
## ndvi_se -0.08095346
## ndvi_sw -0.11693325
## precipitation_amt_mm -18.40839755
## reanalysis_air_temp_k 2.85234170
## reanalysis_avg_temp_k 1.60626304
## reanalysis_dew_point_temp_k 1.32568686
## reanalysis_max_air_temp_k -5.53866050
## reanalysis_min_air_temp_k 7.33221583
## reanalysis_precip_amt_kg_per_m2 -18.76319415
## reanalysis_relative_humidity_percent -9.52172420
## reanalysis_specific_humidity_g_per_kg 1.16514972
## reanalysis_tdtr_k -8.02334173
## station_avg_temp_c 0.38065656
## station_diur_temp_rng_c -4.46029194
## station_max_temp_c -2.02384762
## station_min_temp_c 2.89934853
## reanalysis_precip_amt_kg_per_m2
## weekofyear -25.5226433
## ndvi_ne 1.7401740
## ndvi_nw 1.5352623
## ndvi_se 0.1845527
## ndvi_sw 0.5707464
## precipitation_amt_mm 922.2326877
## reanalysis_air_temp_k -15.1401121
## reanalysis_avg_temp_k -6.8357502
## reanalysis_dew_point_temp_k 31.8063294
## reanalysis_max_air_temp_k 30.3934891
## reanalysis_min_air_temp_k -18.7631941
## reanalysis_precip_amt_kg_per_m2 2086.9035354
## reanalysis_relative_humidity_percent 237.7132635
## reanalysis_specific_humidity_g_per_kg 34.0140047
## reanalysis_tdtr_k 16.6189352
## station_avg_temp_c 7.5884780
## station_diur_temp_rng_c 20.5383086
## station_max_temp_c 21.0599578
## station_min_temp_c -0.2564459
## reanalysis_relative_humidity_percent
## weekofyear -12.1694428
## ndvi_ne 0.5925879
## ndvi_nw 0.5313179
## ndvi_se 0.1196346
## ndvi_sw 0.2166121
## precipitation_amt_mm 174.4169361
## reanalysis_air_temp_k -6.4396400
## reanalysis_avg_temp_k -3.5762123
## reanalysis_dew_point_temp_k 6.7540718
## reanalysis_max_air_temp_k 8.4356552
## reanalysis_min_air_temp_k -9.5217242
## reanalysis_precip_amt_kg_per_m2 237.7132635
## reanalysis_relative_humidity_percent 66.7000759
## reanalysis_specific_humidity_g_per_kg 7.1635386
## reanalysis_tdtr_k 8.8194690
## station_avg_temp_c 1.8906690
## station_diur_temp_rng_c 7.1271442
## station_max_temp_c 6.0226541
## station_min_temp_c -1.2335142
## reanalysis_specific_humidity_g_per_kg
## weekofyear 5.193132784
## ndvi_ne 0.025733999
## ndvi_nw 0.027636208
## ndvi_se 0.002364480
## ndvi_sw 0.007464316
## precipitation_amt_mm 27.752079698
## reanalysis_air_temp_k 0.766866397
## reanalysis_avg_temp_k 0.927298651
## reanalysis_dew_point_temp_k 2.232373339
## reanalysis_max_air_temp_k 1.118371815
## reanalysis_min_air_temp_k 1.165149724
## reanalysis_precip_amt_kg_per_m2 34.014004747
## reanalysis_relative_humidity_percent 7.163538572
## reanalysis_specific_humidity_g_per_kg 2.278906724
## reanalysis_tdtr_k -0.144916593
## station_avg_temp_c 1.211572718
## station_diur_temp_rng_c 0.287496817
## station_max_temp_c 1.359634031
## station_min_temp_c 1.254429508
## reanalysis_tdtr_k station_avg_temp_c
## weekofyear 8.3204076 5.29999147
## ndvi_ne 0.3898208 0.04246468
## ndvi_nw 0.3371359 0.03995233
## ndvi_se 0.1314195 0.01207428
## ndvi_sw 0.1825651 0.01794682
## precipitation_amt_mm 29.4941976 10.84186986
## reanalysis_air_temp_k -1.4621189 0.87764889
## reanalysis_avg_temp_k 0.5829099 1.07103998
## reanalysis_dew_point_temp_k -0.4037208 1.17380311
## reanalysis_max_air_temp_k 11.3932576 2.01775944
## reanalysis_min_air_temp_k -8.0233417 0.38065656
## reanalysis_precip_amt_kg_per_m2 16.6189352 7.58847804
## reanalysis_relative_humidity_percent 8.8194690 1.89066897
## reanalysis_specific_humidity_g_per_kg -0.1449166 1.21157272
## reanalysis_tdtr_k 13.6050564 1.28232844
## station_avg_temp_c 1.2823284 1.49111434
## station_diur_temp_rng_c 7.5740783 1.13627009
## station_max_temp_c 5.0750866 1.82812029
## station_min_temp_c -2.6692421 0.94249298
## station_diur_temp_rng_c
## weekofyear 3.22165834
## ndvi_ne 0.23881804
## ndvi_nw 0.21259710
## ndvi_se 0.07942685
## ndvi_sw 0.11406387
## precipitation_amt_mm 19.79142482
## reanalysis_air_temp_k -0.89530297
## reanalysis_avg_temp_k 0.30536645
## reanalysis_dew_point_temp_k 0.12266006
## reanalysis_max_air_temp_k 6.67889340
## reanalysis_min_air_temp_k -4.46029194
## reanalysis_precip_amt_kg_per_m2 20.53830858
## reanalysis_relative_humidity_percent 7.12714423
## reanalysis_specific_humidity_g_per_kg 0.28749682
## reanalysis_tdtr_k 7.57407833
## station_avg_temp_c 1.13627009
## station_diur_temp_rng_c 5.46415134
## station_max_temp_c 3.65712340
## station_min_temp_c -1.64916763
## station_max_temp_c station_min_temp_c
## weekofyear 6.568820971 3.735729764
## ndvi_ne 0.164905951 -0.078155430
## ndvi_nw 0.147642902 -0.070215578
## ndvi_se 0.049339064 -0.029574449
## ndvi_sw 0.075526240 -0.041898156
## precipitation_amt_mm 25.653316005 3.021408330
## reanalysis_air_temp_k 0.311950943 1.419865389
## reanalysis_avg_temp_k 1.113943164 1.015231537
## reanalysis_dew_point_temp_k 1.234814909 1.301272869
## reanalysis_max_air_temp_k 5.463556909 -1.332094601
## reanalysis_min_air_temp_k -2.023847623 2.899348535
## reanalysis_precip_amt_kg_per_m2 21.059957832 -0.256445885
## reanalysis_relative_humidity_percent 6.022654108 -1.233514188
## reanalysis_specific_humidity_g_per_kg 1.359634031 1.254429508
## reanalysis_tdtr_k 5.075086586 -2.669242066
## station_avg_temp_c 1.828120293 0.942492979
## station_diur_temp_rng_c 3.657123395 -1.649167634
## station_max_temp_c 4.047336402 0.005596358
## station_min_temp_c 0.005596358 2.290012831## [1] 2.952405e+03 1.068214e+03 2.282492e+02 4.635100e+01 2.378743e+01
## [6] 9.348615e+00 1.332368e+00 8.807503e-01 4.750826e-01 3.684911e-01
## [11] 2.452523e-01 1.395691e-01 2.532241e-02 1.864853e-02 5.815935e-03
## [16] 4.828136e-03 3.730421e-03 2.524490e-03 1.300312e-03## [1] 54.33604091 32.68353829 15.10791834 6.80815690 4.87723629 3.05755055
## [7] 1.15428258 0.93848300 0.68926232 0.60703472 0.49522950 0.37358948
## [13] 0.15913017 0.13655961 0.07626228 0.06948479 0.06107717 0.05024431
## [19] 0.03605984## [,1] [,2] [,3] [,4] [,5]
## [1,] -1.336773e-03 -5.188413e-02 0.9911007667 0.009343769 -0.082440395
## [2,] -8.155553e-04 -5.958909e-06 0.0006825361 0.014209603 0.008797233
## [3,] -7.189542e-04 -1.427280e-06 0.0005168697 0.012551961 0.007314127
## [4,] -9.652485e-05 -3.057648e-05 0.0009082450 0.004506543 0.003487444
## [5,] -2.532568e-04 4.176366e-05 0.0006860482 0.006407128 0.004859470
## [6,] -6.650019e-01 -7.437786e-01 -0.0391268529 -0.051527622 0.015356951
## [7,] 5.770298e-03 -4.593536e-03 0.0361564840 -0.109200540 0.028580501
## [8,] 1.814452e-03 -4.803035e-03 0.0386608197 -0.038364047 0.077777713
## [9,] -1.413978e-02 1.452668e-03 0.0224407474 0.022850689 -0.128762639
## [10,] -1.591791e-02 -5.951305e-03 0.0640603051 0.311556170 0.412301279
## [11,] 9.268243e-03 7.646756e-04 0.0194617792 -0.291471143 -0.227890253
## [12,] -7.391379e-01 6.656002e-01 0.0379188829 -0.079550763 0.052140153
## [13,] -1.013240e-01 2.896002e-02 -0.0552234381 0.741857065 -0.624517639
## [14,] -1.504487e-02 1.795096e-03 0.0232428865 0.030319879 -0.120792196
## [15,] -1.129552e-02 -1.057617e-02 0.0373911802 0.388355413 0.479926657
## [16,] -4.446425e-03 -3.071616e-03 0.0238671645 0.038286543 0.026511817
## [17,] -9.962320e-03 -1.080747e-03 0.0158308352 0.241144823 0.263291769
## [18,] -1.135775e-02 -5.007811e-03 0.0298326775 0.159421645 0.158298381
## [19,] -5.546937e-04 -2.455635e-03 0.0161945218 -0.086278558 -0.121176302
## [,6] [,7] [,8] [,9] [,10]
## [1,] 0.0878740538 -0.0179956560 0.0074873655 0.0037595360 -0.001762315
## [2,] 0.0021018583 -0.0008756333 0.0083195216 0.0026962816 -0.013072197
## [3,] 0.0007182355 -0.0043756171 0.0007831003 0.0035792849 -0.007768804
## [4,] 0.0011423955 0.0005990927 -0.0048179799 0.0002096883 -0.006466135
## [5,] 0.0007987164 -0.0015394713 -0.0050182637 -0.0035292626 -0.006970663
## [6,] 0.0115624954 -0.0020527438 -0.0009418687 0.0002503250 -0.001989924
## [7,] -0.3282912295 0.0863777519 -0.1110268274 0.0827790035 0.234248110
## [8,] -0.3329880417 0.1556482407 -0.1921876717 0.1387329408 0.182618869
## [9,] -0.3284767595 0.0893477636 -0.1262429356 0.0699549003 0.242416978
## [10,] -0.2668133686 0.3330813265 -0.1311703278 -0.5652972482 -0.405852410
## [11,] -0.4037933946 -0.0324041782 -0.4325345288 0.0144270226 -0.319527872
## [12,] 0.0105922138 -0.0007308008 0.0056128065 0.0038074181 0.001568350
## [13,] -0.0202573827 0.0351826351 -0.0524393223 -0.0064329547 -0.041648648
## [14,] -0.3304332008 0.0890126577 -0.1296736592 0.0749402697 0.258448401
## [15,] 0.0130406892 0.3296431185 0.0142938372 0.4719590218 0.212029906
## [16,] -0.3147676648 -0.1968481229 0.3319146679 0.2283413302 -0.047693480
## [17,] -0.0735225164 -0.6135656446 -0.2930333315 0.3747481172 -0.383635938
## [18,] -0.3344878145 -0.5201628403 0.3103130807 -0.4223096710 0.365501315
## [19,] -0.3241926853 0.2106609398 0.6466851419 0.2232769803 -0.435129290
## [,11] [,12] [,13] [,14] [,15]
## [1,] -0.0042776449 -2.063707e-05 -1.780625e-03 -1.030259e-03 1.724124e-04
## [2,] -0.0100087080 1.102509e-02 -8.023025e-02 6.419518e-01 -6.444234e-02
## [3,] -0.0081282786 1.667613e-02 -5.866768e-02 5.251488e-01 -6.986079e-02
## [4,] 0.0051471045 2.646813e-05 -4.924812e-02 3.557515e-01 4.299777e-03
## [5,] -0.0001346428 3.094802e-03 -5.164606e-02 4.005660e-01 1.078783e-02
## [6,] 0.0009393750 4.480752e-04 -3.669309e-04 7.996515e-05 -2.059608e-05
## [7,] 0.2082610003 -1.368247e-01 1.822674e-01 1.610072e-03 -7.448210e-01
## [8,] 0.0332206362 -9.771462e-02 -8.596560e-01 -9.758183e-02 6.836042e-02
## [9,] 0.2116347397 -1.348792e-01 2.906827e-01 -1.395784e-03 -2.630009e-03
## [10,] 0.1966999789 6.367409e-02 4.428556e-02 -8.955116e-03 1.082406e-02
## [11,] -0.5742642519 2.531069e-01 1.222678e-01 1.148341e-02 4.733542e-03
## [12,] -0.0020897234 9.265732e-04 -9.595581e-06 1.279084e-05 -3.201459e-05
## [13,] -0.0631811840 3.242696e-02 -9.478494e-02 -2.623108e-02 -1.382364e-01
## [14,] 0.2244310491 -1.513691e-01 2.676060e-01 1.195466e-01 6.416956e-01
## [15,] -0.4459420239 1.105449e-01 1.708283e-01 4.881594e-03 7.685284e-03
## [16,] 0.3177818370 7.696087e-01 -3.180473e-02 -1.658812e-02 1.381296e-02
## [17,] 0.1787270040 -2.905267e-01 1.740983e-02 -8.645576e-03 4.778965e-03
## [18,] -0.3800528539 -1.140474e-01 -1.706496e-02 -2.994647e-03 2.020046e-03
## [19,] -0.1070215481 -3.988938e-01 -1.724606e-03 1.514100e-03 9.716692e-03
## [,16] [,17] [,18] [,19]
## [1,] 4.002689e-04 4.382591e-05 -1.308792e-04 -2.489697e-04
## [2,] 3.921174e-01 1.257232e-01 6.295719e-01 -1.031035e-01
## [3,] 3.407600e-01 8.237229e-02 -7.614129e-01 1.122260e-01
## [4,] -5.527636e-01 -4.474637e-02 1.061663e-01 7.430003e-01
## [5,] -6.213983e-01 -1.277099e-01 -1.081713e-01 -6.499634e-01
## [6,] -9.205675e-05 -9.992982e-06 -1.378975e-05 -4.470817e-06
## [7,] 2.989877e-02 -3.808940e-01 1.982854e-02 1.286903e-02
## [8,] 2.955863e-03 4.893631e-02 -6.329680e-03 -4.318673e-03
## [9,] -1.468550e-01 7.847375e-01 -1.878979e-02 -3.867928e-02
## [10,] 3.645339e-03 3.748569e-03 -7.854894e-04 8.586225e-04
## [11,] -3.424888e-04 -1.349560e-02 4.229494e-03 2.748171e-03
## [12,] -2.192788e-04 5.191768e-04 -4.741421e-05 3.883496e-05
## [13,] 3.634006e-03 -7.372436e-02 3.784330e-03 3.025641e-03
## [14,] 1.254703e-01 -4.359902e-01 5.846401e-03 2.366435e-02
## [15,] -1.045363e-02 2.999145e-03 1.717556e-03 1.047707e-03
## [16,] -6.779649e-03 -1.910295e-03 3.575001e-03 -2.151452e-04
## [17,] 1.930168e-03 8.315087e-03 8.688209e-04 -1.605308e-03
## [18,] -5.535950e-03 2.513045e-03 3.776636e-04 3.404626e-03
## [19,] -3.850848e-03 1.102120e-03 -6.880374e-03 -2.109782e-04## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 54.3360 32.6835 15.10792 6.8082 4.87724 3.05755 1.15428
## Proportion of Variance 0.6816 0.2466 0.05269 0.0107 0.00549 0.00216 0.00031
## Cumulative Proportion 0.6816 0.9282 0.98084 0.9915 0.99703 0.99919 0.99950
## PC8 PC9 PC10 PC11 PC12 PC13 PC14
## Standard deviation 0.9385 0.68926 0.60703 0.49523 0.37359 0.15913 0.1366
## Proportion of Variance 0.0002 0.00011 0.00009 0.00006 0.00003 0.00001 0.0000
## Cumulative Proportion 0.9997 0.99981 0.99990 0.99995 0.99999 0.99999 1.0000
## PC15 PC16 PC17 PC18 PC19
## Standard deviation 0.07626 0.06948 0.06108 0.05024 0.03606
## Proportion of Variance 0.00000 0.00000 0.00000 0.00000 0.00000
## Cumulative Proportion 1.00000 1.00000 1.00000 1.00000 1.00000## PC1 PC2 PC3
## weekofyear -1.336773e-03 -5.188413e-02 0.9911007667
## ndvi_ne -8.155553e-04 -5.958909e-06 0.0006825361
## ndvi_nw -7.189542e-04 -1.427280e-06 0.0005168697
## ndvi_se -9.652485e-05 -3.057648e-05 0.0009082450
## ndvi_sw -2.532568e-04 4.176366e-05 0.0006860482
## precipitation_amt_mm -6.650019e-01 -7.437786e-01 -0.0391268529
## reanalysis_air_temp_k 5.770298e-03 -4.593536e-03 0.0361564840
## reanalysis_avg_temp_k 1.814452e-03 -4.803035e-03 0.0386608197
## reanalysis_dew_point_temp_k -1.413978e-02 1.452668e-03 0.0224407474
## reanalysis_max_air_temp_k -1.591791e-02 -5.951305e-03 0.0640603051
## reanalysis_min_air_temp_k 9.268243e-03 7.646756e-04 0.0194617792
## reanalysis_precip_amt_kg_per_m2 -7.391379e-01 6.656002e-01 0.0379188829
## reanalysis_relative_humidity_percent -1.013240e-01 2.896002e-02 -0.0552234381
## reanalysis_specific_humidity_g_per_kg -1.504487e-02 1.795096e-03 0.0232428865
## reanalysis_tdtr_k -1.129552e-02 -1.057617e-02 0.0373911802
## station_avg_temp_c -4.446425e-03 -3.071616e-03 0.0238671645
## station_diur_temp_rng_c -9.962320e-03 -1.080747e-03 0.0158308352
## station_max_temp_c -1.135775e-02 -5.007811e-03 0.0298326775
## station_min_temp_c -5.546937e-04 -2.455635e-03 0.0161945218
## PC4 PC5 PC6
## weekofyear -0.009343769 0.082440395 0.0878740538
## ndvi_ne -0.014209603 -0.008797233 0.0021018583
## ndvi_nw -0.012551961 -0.007314127 0.0007182355
## ndvi_se -0.004506543 -0.003487444 0.0011423955
## ndvi_sw -0.006407128 -0.004859470 0.0007987164
## precipitation_amt_mm 0.051527622 -0.015356951 0.0115624954
## reanalysis_air_temp_k 0.109200540 -0.028580501 -0.3282912295
## reanalysis_avg_temp_k 0.038364047 -0.077777713 -0.3329880417
## reanalysis_dew_point_temp_k -0.022850689 0.128762639 -0.3284767595
## reanalysis_max_air_temp_k -0.311556170 -0.412301279 -0.2668133686
## reanalysis_min_air_temp_k 0.291471143 0.227890253 -0.4037933946
## reanalysis_precip_amt_kg_per_m2 0.079550763 -0.052140153 0.0105922138
## reanalysis_relative_humidity_percent -0.741857065 0.624517639 -0.0202573827
## reanalysis_specific_humidity_g_per_kg -0.030319879 0.120792196 -0.3304332008
## reanalysis_tdtr_k -0.388355413 -0.479926657 0.0130406892
## station_avg_temp_c -0.038286543 -0.026511817 -0.3147676648
## station_diur_temp_rng_c -0.241144823 -0.263291769 -0.0735225164
## station_max_temp_c -0.159421645 -0.158298381 -0.3344878145
## station_min_temp_c 0.086278558 0.121176302 -0.3241926853
## PC7 PC8 PC9
## weekofyear -0.0179956560 -0.0074873655 0.0037595360
## ndvi_ne -0.0008756333 -0.0083195216 0.0026962816
## ndvi_nw -0.0043756171 -0.0007831003 0.0035792849
## ndvi_se 0.0005990927 0.0048179799 0.0002096883
## ndvi_sw -0.0015394713 0.0050182637 -0.0035292626
## precipitation_amt_mm -0.0020527438 0.0009418687 0.0002503250
## reanalysis_air_temp_k 0.0863777519 0.1110268274 0.0827790035
## reanalysis_avg_temp_k 0.1556482407 0.1921876717 0.1387329408
## reanalysis_dew_point_temp_k 0.0893477636 0.1262429356 0.0699549003
## reanalysis_max_air_temp_k 0.3330813265 0.1311703278 -0.5652972482
## reanalysis_min_air_temp_k -0.0324041782 0.4325345288 0.0144270226
## reanalysis_precip_amt_kg_per_m2 -0.0007308008 -0.0056128065 0.0038074181
## reanalysis_relative_humidity_percent 0.0351826351 0.0524393223 -0.0064329547
## reanalysis_specific_humidity_g_per_kg 0.0890126577 0.1296736592 0.0749402697
## reanalysis_tdtr_k 0.3296431185 -0.0142938372 0.4719590218
## station_avg_temp_c -0.1968481229 -0.3319146679 0.2283413302
## station_diur_temp_rng_c -0.6135656446 0.2930333315 0.3747481172
## station_max_temp_c -0.5201628403 -0.3103130807 -0.4223096710
## station_min_temp_c 0.2106609398 -0.6466851419 0.2232769803
## PC10 PC11 PC12
## weekofyear -0.001762315 -0.0042776449 -2.063707e-05
## ndvi_ne -0.013072197 -0.0100087080 1.102509e-02
## ndvi_nw -0.007768804 -0.0081282786 1.667613e-02
## ndvi_se -0.006466135 0.0051471045 2.646813e-05
## ndvi_sw -0.006970663 -0.0001346428 3.094802e-03
## precipitation_amt_mm -0.001989924 0.0009393750 4.480752e-04
## reanalysis_air_temp_k 0.234248110 0.2082610003 -1.368247e-01
## reanalysis_avg_temp_k 0.182618869 0.0332206362 -9.771462e-02
## reanalysis_dew_point_temp_k 0.242416978 0.2116347397 -1.348792e-01
## reanalysis_max_air_temp_k -0.405852410 0.1966999789 6.367409e-02
## reanalysis_min_air_temp_k -0.319527872 -0.5742642519 2.531069e-01
## reanalysis_precip_amt_kg_per_m2 0.001568350 -0.0020897234 9.265732e-04
## reanalysis_relative_humidity_percent -0.041648648 -0.0631811840 3.242696e-02
## reanalysis_specific_humidity_g_per_kg 0.258448401 0.2244310491 -1.513691e-01
## reanalysis_tdtr_k 0.212029906 -0.4459420239 1.105449e-01
## station_avg_temp_c -0.047693480 0.3177818370 7.696087e-01
## station_diur_temp_rng_c -0.383635938 0.1787270040 -2.905267e-01
## station_max_temp_c 0.365501315 -0.3800528539 -1.140474e-01
## station_min_temp_c -0.435129290 -0.1070215481 -3.988938e-01
## PC13 PC14 PC15
## weekofyear 1.780625e-03 1.030259e-03 -1.724124e-04
## ndvi_ne 8.023025e-02 -6.419518e-01 6.444234e-02
## ndvi_nw 5.866768e-02 -5.251488e-01 6.986079e-02
## ndvi_se 4.924812e-02 -3.557515e-01 -4.299777e-03
## ndvi_sw 5.164606e-02 -4.005660e-01 -1.078783e-02
## precipitation_amt_mm 3.669309e-04 -7.996515e-05 2.059608e-05
## reanalysis_air_temp_k -1.822674e-01 -1.610072e-03 7.448210e-01
## reanalysis_avg_temp_k 8.596560e-01 9.758183e-02 -6.836042e-02
## reanalysis_dew_point_temp_k -2.906827e-01 1.395784e-03 2.630009e-03
## reanalysis_max_air_temp_k -4.428556e-02 8.955116e-03 -1.082406e-02
## reanalysis_min_air_temp_k -1.222678e-01 -1.148341e-02 -4.733542e-03
## reanalysis_precip_amt_kg_per_m2 9.595581e-06 -1.279084e-05 3.201459e-05
## reanalysis_relative_humidity_percent 9.478494e-02 2.623108e-02 1.382364e-01
## reanalysis_specific_humidity_g_per_kg -2.676060e-01 -1.195466e-01 -6.416956e-01
## reanalysis_tdtr_k -1.708283e-01 -4.881594e-03 -7.685284e-03
## station_avg_temp_c 3.180473e-02 1.658812e-02 -1.381296e-02
## station_diur_temp_rng_c -1.740983e-02 8.645576e-03 -4.778965e-03
## station_max_temp_c 1.706496e-02 2.994647e-03 -2.020046e-03
## station_min_temp_c 1.724606e-03 -1.514100e-03 -9.716692e-03
## PC16 PC17 PC18
## weekofyear -4.002689e-04 4.382591e-05 1.308792e-04
## ndvi_ne -3.921174e-01 1.257232e-01 -6.295719e-01
## ndvi_nw -3.407600e-01 8.237229e-02 7.614129e-01
## ndvi_se 5.527636e-01 -4.474637e-02 -1.061663e-01
## ndvi_sw 6.213983e-01 -1.277099e-01 1.081713e-01
## precipitation_amt_mm 9.205675e-05 -9.992982e-06 1.378975e-05
## reanalysis_air_temp_k -2.989877e-02 -3.808940e-01 -1.982854e-02
## reanalysis_avg_temp_k -2.955863e-03 4.893631e-02 6.329680e-03
## reanalysis_dew_point_temp_k 1.468550e-01 7.847375e-01 1.878979e-02
## reanalysis_max_air_temp_k -3.645339e-03 3.748569e-03 7.854894e-04
## reanalysis_min_air_temp_k 3.424888e-04 -1.349560e-02 -4.229494e-03
## reanalysis_precip_amt_kg_per_m2 2.192788e-04 5.191768e-04 4.741421e-05
## reanalysis_relative_humidity_percent -3.634006e-03 -7.372436e-02 -3.784330e-03
## reanalysis_specific_humidity_g_per_kg -1.254703e-01 -4.359902e-01 -5.846401e-03
## reanalysis_tdtr_k 1.045363e-02 2.999145e-03 -1.717556e-03
## station_avg_temp_c 6.779649e-03 -1.910295e-03 -3.575001e-03
## station_diur_temp_rng_c -1.930168e-03 8.315087e-03 -8.688209e-04
## station_max_temp_c 5.535950e-03 2.513045e-03 -3.776636e-04
## station_min_temp_c 3.850848e-03 1.102120e-03 6.880374e-03
## PC19
## weekofyear -2.489697e-04
## ndvi_ne -1.031035e-01
## ndvi_nw 1.122260e-01
## ndvi_se 7.430003e-01
## ndvi_sw -6.499634e-01
## precipitation_amt_mm -4.470817e-06
## reanalysis_air_temp_k 1.286903e-02
## reanalysis_avg_temp_k -4.318673e-03
## reanalysis_dew_point_temp_k -3.867928e-02
## reanalysis_max_air_temp_k 8.586225e-04
## reanalysis_min_air_temp_k 2.748171e-03
## reanalysis_precip_amt_kg_per_m2 3.883496e-05
## reanalysis_relative_humidity_percent 3.025641e-03
## reanalysis_specific_humidity_g_per_kg 2.366435e-02
## reanalysis_tdtr_k 1.047707e-03
## station_avg_temp_c -2.151452e-04
## station_diur_temp_rng_c -1.605308e-03
## station_max_temp_c 3.404626e-03
## station_min_temp_c -2.109782e-04Autovalores :
En resumen, puedes concluir que los primeros componentes principales
(los asociados con los autovalores más grandes) son los más importantes
para representar la variabilidad en tus datos. En este caso, el primer
componente principal es significativamente más importante que los
siguientes, lo que indica que captura la mayoría de la variabilidad en
los datos.
Standard deviation : PC1 tiene la desviación estándar más alta (54.3360), lo que significa que explica la mayor parte de la varianza en los datos. PC2 tiene la segunda desviación estándar más alta (32.6835), por lo que explica la segunda mayor cantidad de varianza. Los componentes restantes explican cada vez menos varianza, hasta PC17, que tiene la desviación estándar más baja (0.06108) y por lo tanto explica la menor cantidad de varianza. En resumen, los componentes con las desviaciones estándar más altas son los más importantes para explicar la varianza en los datos. Los componentes con desviaciones estándar más bajas son menos importantes. Esto es útil para reducir la dimensionalidad de los datos
Proportion of Variance PC1 explica el 68.16% de la varianza total, lo que significa que es el componente más importante. PC2 explica el 24.66% de la varianza total, siendo el segundo componente más importante. PC3 explica el 5.269% de la varianza total. Los componentes restantes explican cada vez menos varianza, hasta PC17, que prácticamente no explica ninguna varianza (0.000%).
Cumulative Proportion: Estos valores representan la proporción acumulada de la varianza total explicada por cada componente principal (PC1 a PC17) en un análisis de componentes principales (PCA). PC1 explica el 68.16% de la varianza total. Al agregar PC2, se explica el 92.82% de la varianza total. Al agregar PC3, se explica el 98.084% de la varianza total. Y así sucesivamente, hasta que al agregar todos los componentes hasta PC17, se explica el 100% de la varianza total. En resumen, puedes ver cuánta varianza se explica al agregar cada componente principal sucesivamente. Esto es útil para determinar cuántos componentes principales necesitas para explicar una cierta cantidad de varianza.
3. Número de componentes a extraer
3.1 Gráfico de sedimentación (Scree-plot)
Punto de Inflexión: El “codo” en el componente 2 sugiere que los primeros dos componentes principales (PC1 y PC2) son significativos y explican la mayoría de la varianza. Contribución de Componentes: Los componentes después del “codo” tienen una contribución marginal a la varianza total, lo que implica que podrían no ser necesarios para la mayoría de las aplicaciones. Selección de Componentes: Basado en este gráfico, se podría considerar retener solo los primeros dos componentes para simplificar el modelo sin perder mucha información.
4. Gráficos para relacionar componentes con variables
## Warning in arrows(0, 0, y[, 1L] * 0.8, y[, 2L] * 0.8, col = col[2L], length =
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Agrupación Densa: Hay una agrupación densa de puntos alrededor del origen, lo que podría indicar que muchas observaciones tienen valores similares para los componentes principales representados.
Outliers: Algunos puntos se extienden a lo largo de los ejes PC1 y PC2, lo que sugiere que hay observaciones con valores atípicos en estas dimensiones.
Variables Significativas: Las variables “precip_amt_kg_per_m2” y “precipitation_amt_mm” están resaltadas, lo que indica su importancia en el conjunto de datos. Con base en esta información, se puede concluir que el biplot ayuda a identificar las relaciones entre las variables y las observaciones, así como a detectar patrones y outliers en los datos. Es una herramienta útil para la interpretación de un análisis de componentes principales (PCA).
Análisis Decriptivo
## [1] 4331.859## [1] 4331.859
Interacciones entre Variables: Las líneas o conexiones entre los nodos (variables) indican la fueridad y dirección de la correlación entre ellas.
Clusters: La agrupación de nodos puede sugerir que ciertas variables están altamente correlacionadas entre sí.
Outliers: Los nodos que no están densamente conectados o que están alejados de los clusters principales pueden indicar variables con menos correlaciones fuertes.
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## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
## Warning in par(usr): argument 1 does not name a graphical parameter
s_1= cov(data_numerica)
#sin dividir a los datos por su desviación
res_1 = prcomp(data_numerica)
summary(res_1)## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 54.3360 32.6835 15.10792 6.8082 4.87724 3.05755 1.15428
## Proportion of Variance 0.6816 0.2466 0.05269 0.0107 0.00549 0.00216 0.00031
## Cumulative Proportion 0.6816 0.9282 0.98084 0.9915 0.99703 0.99919 0.99950
## PC8 PC9 PC10 PC11 PC12 PC13 PC14
## Standard deviation 0.9385 0.68926 0.60703 0.49523 0.37359 0.15913 0.1366
## Proportion of Variance 0.0002 0.00011 0.00009 0.00006 0.00003 0.00001 0.0000
## Cumulative Proportion 0.9997 0.99981 0.99990 0.99995 0.99999 0.99999 1.0000
## PC15 PC16 PC17 PC18 PC19
## Standard deviation 0.07626 0.06948 0.06108 0.05024 0.03606
## Proportion of Variance 0.00000 0.00000 0.00000 0.00000 0.00000
## Cumulative Proportion 1.00000 1.00000 1.00000 1.00000 1.00000## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 2.6432 2.1790 1.6098 1.1062 0.91504 0.77701 0.71418
## Proportion of Variance 0.3677 0.2499 0.1364 0.0644 0.04407 0.03178 0.02684
## Cumulative Proportion 0.3677 0.6176 0.7540 0.8184 0.86249 0.89426 0.92111
## PC8 PC9 PC10 PC11 PC12 PC13 PC14
## Standard deviation 0.6118 0.55219 0.49198 0.4338 0.34855 0.32000 0.28209
## Proportion of Variance 0.0197 0.01605 0.01274 0.0099 0.00639 0.00539 0.00419
## Cumulative Proportion 0.9408 0.95685 0.96959 0.9795 0.98589 0.99128 0.99547
## PC15 PC16 PC17 PC18 PC19
## Standard deviation 0.21146 0.1687 0.09806 0.04489 0.03575
## Proportion of Variance 0.00235 0.0015 0.00051 0.00011 0.00007
## Cumulative Proportion 0.99782 0.9993 0.99983 0.99993 1.00000## Class: pca dudi
## Call: dudi.pca(df = data_numerica, scannf = F, nf = 2)
##
## Total inertia: 19
##
## Eigenvalues:
## Ax1 Ax2 Ax3 Ax4 Ax5
## 6.9867 4.7481 2.5916 1.2236 0.8373
##
## Projected inertia (%):
## Ax1 Ax2 Ax3 Ax4 Ax5
## 36.772 24.990 13.640 6.440 4.407
##
## Cumulative projected inertia (%):
## Ax1 Ax1:2 Ax1:3 Ax1:4 Ax1:5
## 36.77 61.76 75.40 81.84 86.25
##
## (Only 5 dimensions (out of 19) are shown)## Inertia information:
## Call: inertia.dudi(x = acp)
##
## Decomposition of total inertia:
## inertia cum cum(%)
## Ax1 6.986688 6.987 36.77
## Ax2 4.748088 11.735 61.76
## Ax3 2.591565 14.326 75.40
## Ax4 1.223606 15.550 81.84
## Ax5 0.837294 16.387 86.25
## Ax6 0.603740 16.991 89.43
## Ax7 0.510050 17.501 92.11
## Ax8 0.374291 17.875 94.08
## Ax9 0.304917 18.180 95.69
## Ax10 0.242044 18.422 96.96
## Ax11 0.188184 18.610 97.95
## Ax12 0.121485 18.732 98.59
## Ax13 0.102397 18.834 99.13
## Ax14 0.079575 18.914 99.55
## Ax15 0.044717 18.959 99.78
## Ax16 0.028449 18.987 99.93
## Ax17 0.009616 18.997 99.98
## Ax18 0.002015 18.999 99.99
## Ax19 0.001278 19.000 100.00## [1] 13.5437
## Loading required package: ggplot2##
## Attaching package: 'ggplot2'## The following objects are masked from 'package:psych':
##
## %+%, alpha## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
Puntuaciones
pun1 = as.matrix(scale(data_numerica, center = T, scale = F))%*%as.matrix(eigen(s)$vectors)
datosf1 = pun1[,1:2]
cor(datosf1)## [,1] [,2]
## [1,] 1.000000e+00 4.263451e-16
## [2,] 4.263451e-16 1.000000e+00## PC1 PC2
## PC1 1.000000e+00 8.846661e-17
## PC2 8.846661e-17 1.000000e+00## Axis1 Axis2
## Axis1 1.000000e+00 8.574075e-16
## Axis2 8.574075e-16 1.000000e+00fviz_pca_ind(acp) #dibuja todos los datos, entre los dos ejes puedes cuanto % de variabilidad mantienes
