promedios.art <- read.delim("~/CONGRESO/Articulos INIFAP/promedios art.txt")
data <- promedios.art
attach(data)
#Correlaccion de los datos
cor(promedios.art[,2:19])
## PF PS NH NFM NFH AF
## PF 1.00000000 0.9410264 0.94114375 0.94114375 0.9103095 0.9015621
## PS 0.94102641 1.0000000 0.98951409 0.98951409 0.9747959 0.9935741
## NH 0.94114375 0.9895141 1.00000000 1.00000000 0.9494473 0.9816959
## NFM 0.94114375 0.9895141 1.00000000 1.00000000 0.9494473 0.9816959
## NFH 0.91030947 0.9747959 0.94944734 0.94944734 1.0000000 0.9801645
## AF 0.90156209 0.9935741 0.98169587 0.98169587 0.9801645 1.0000000
## PHOTO 0.86391722 0.8859626 0.89261774 0.89261774 0.7881745 0.8564946
## TRAN 0.93265202 0.9724719 0.94705929 0.94705929 0.9850328 0.9662611
## UEAF -0.71459991 -0.6826058 -0.65713906 -0.65713906 -0.7667072 -0.6767363
## ATFL -0.64325954 -0.5272622 -0.47557179 -0.47557179 -0.6657923 -0.5090836
## ATF 0.15796057 0.1699392 0.21953768 0.21953768 0.2970153 0.2211656
## ATFR 0.07351669 -0.1185380 -0.04540389 -0.04540389 -0.2105781 -0.1759166
## ORP -0.70663362 -0.5423938 -0.46815538 -0.46815538 -0.5696982 -0.4727952
## SST 0.02672959 0.2353630 0.21191260 0.21191260 0.1647510 0.2650490
## NFTO 0.51269415 0.6810782 0.63341897 0.63341897 0.5818679 0.6824269
## PFTO 0.74784241 0.8416368 0.82206777 0.82206777 0.7257869 0.8202858
## COND 0.97143101 0.9869109 0.97320616 0.97320616 0.9725475 0.9693630
## CI 0.74189748 0.6903433 0.67348496 0.67348496 0.7667870 0.6788603
## PHOTO TRAN UEAF ATFL ATF
## PF 0.863917215 0.9326520 -0.71459991 -0.64325954 0.157960571
## PS 0.885962610 0.9724719 -0.68260579 -0.52726220 0.169939217
## NH 0.892617740 0.9470593 -0.65713906 -0.47557179 0.219537680
## NFM 0.892617740 0.9470593 -0.65713906 -0.47557179 0.219537680
## NFH 0.788174547 0.9850328 -0.76670722 -0.66579229 0.297015268
## AF 0.856494643 0.9662611 -0.67673629 -0.50908362 0.221165555
## PHOTO 1.000000000 0.7689318 -0.30750744 -0.27672873 0.005130772
## TRAN 0.768931793 1.0000000 -0.82666840 -0.66159747 0.188697819
## UEAF -0.307507438 -0.8266684 1.00000000 0.78499431 -0.268223908
## ATFL -0.276728733 -0.6615975 0.78499431 1.00000000 -0.452546344
## ATF 0.005130772 0.1886978 -0.26822391 -0.45254634 1.000000000
## ATFR 0.263978684 -0.2613380 0.48452142 0.11042400 0.157721800
## ORP -0.487113429 -0.6246609 0.58429959 0.76269452 0.175823940
## SST 0.081133319 0.2444531 -0.20411066 0.36589601 -0.529735232
## NFTO 0.786833373 0.5678366 -0.07887515 0.05454539 -0.384065720
## PFTO 0.883400982 0.7557869 -0.34792540 -0.09549574 -0.334447342
## COND 0.844341393 0.9884868 -0.76657195 -0.61928984 0.158498051
## CI 0.332133926 0.8278925 -0.99680858 -0.79095065 0.288167091
## ATFR ORP SST NFTO PFTO
## PF 0.07351669 -0.70663362 0.02672959 0.51269415 0.74784241
## PS -0.11853797 -0.54239381 0.23536301 0.68107820 0.84163684
## NH -0.04540389 -0.46815538 0.21191260 0.63341897 0.82206777
## NFM -0.04540389 -0.46815538 0.21191260 0.63341897 0.82206777
## NFH -0.21057808 -0.56969820 0.16475103 0.58186792 0.72578691
## AF -0.17591657 -0.47279523 0.26504899 0.68242688 0.82028584
## PHOTO 0.26397868 -0.48711343 0.08113332 0.78683337 0.88340098
## TRAN -0.26133799 -0.62466085 0.24445306 0.56783665 0.75578687
## UEAF 0.48452142 0.58429959 -0.20411066 -0.07887515 -0.34792540
## ATFL 0.11042400 0.76269452 0.36589601 0.05454539 -0.09549574
## ATF 0.15772180 0.17582394 -0.52973523 -0.38406572 -0.33444734
## ATFR 1.00000000 -0.01662966 -0.73142091 -0.12378900 -0.10982226
## ORP -0.01662966 1.00000000 0.16272375 -0.29982896 -0.43521942
## SST -0.73142091 0.16272375 1.00000000 0.49420685 0.51652280
## NFTO -0.12378900 -0.29982896 0.49420685 1.00000000 0.91757655
## PFTO -0.10982226 -0.43521942 0.51652280 0.91757655 1.00000000
## COND -0.13000304 -0.63783386 0.19622389 0.59832290 0.79923570
## CI -0.41893587 -0.59312399 0.15996993 0.05836475 0.34654693
## COND CI
## PF 0.9714310 0.74189748
## PS 0.9869109 0.69034327
## NH 0.9732062 0.67348496
## NFM 0.9732062 0.67348496
## NFH 0.9725475 0.76678697
## AF 0.9693630 0.67886035
## PHOTO 0.8443414 0.33213393
## TRAN 0.9884868 0.82789246
## UEAF -0.7665719 -0.99680858
## ATFL -0.6192898 -0.79095065
## ATF 0.1584981 0.28816709
## ATFR -0.1300030 -0.41893587
## ORP -0.6378339 -0.59312399
## SST 0.1962239 0.15996993
## NFTO 0.5983229 0.05836475
## PFTO 0.7992357 0.34654693
## COND 1.0000000 0.77748513
## CI 0.7774851 1.00000000
# Componentes principales y estandarizar los datos.
PCs <- prcomp(data[-1],scale=T)
PCs
## Standard deviations:
## [1] 3.387860e+00 1.702444e+00 1.447905e+00 1.083255e+00 5.951631e-01
## [6] 1.472114e-15
##
## Rotation:
## PC1 PC2 PC3 PC4 PC5
## PF 0.28318139 0.05873979 -0.12676408 -0.0986834614 -0.26286954
## PS 0.29198342 -0.04553725 -0.04987881 0.0919911890 0.03050520
## NH 0.28615525 -0.03980155 -0.08689315 0.1648887118 -0.14872426
## NFM 0.28615525 -0.03980155 -0.08689315 0.1648887118 -0.14872426
## NFH 0.28901048 0.05067490 0.01157256 0.1071653735 0.23827328
## AF 0.28792399 -0.04790649 -0.02250700 0.1720928839 0.13056596
## PHOTO 0.24789845 -0.16754462 -0.31886112 -0.0003973931 -0.02070010
## TRAN 0.29291281 0.03523919 0.07036698 0.0219668271 0.04446957
## UEAF -0.22561904 -0.24249812 -0.32673360 0.0446479601 0.23260831
## ATFL -0.18194252 -0.41765368 -0.05339944 0.2364973502 -0.34792888
## ATF 0.04348250 0.42175951 -0.13199115 0.5883847209 0.23748960
## ATFR -0.04888228 0.07471890 -0.65286595 -0.0822027898 -0.39367048
## ORP -0.18748635 -0.14101628 0.03425344 0.6713626458 -0.14601578
## SST 0.06521129 -0.40909876 0.45554309 0.1174575474 -0.20499374
## NFTO 0.18389610 -0.41587883 -0.09763338 -0.0525287428 0.49659489
## PFTO 0.23855494 -0.33821638 -0.05974657 -0.0747486886 -0.05936707
## COND 0.29474188 0.01177051 -0.01629098 -0.0018224501 -0.07415180
## CI 0.22763040 0.25631290 0.28940566 -0.0456858181 -0.32247823
## PC6
## PF 0.029567522
## PS -0.013159139
## NH -0.108680842
## NFM -0.042585007
## NFH 0.006527531
## AF -0.135420913
## PHOTO 0.533232079
## TRAN -0.052429021
## UEAF -0.415957108
## ATFL -0.065992367
## ATF -0.088320729
## ATFR -0.256369640
## ORP 0.128723152
## SST -0.074667401
## NFTO -0.297251075
## PFTO -0.009366363
## COND 0.177458363
## CI -0.535609356
summary (PCs)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6
## Standard deviation 3.3879 1.7024 1.4479 1.08326 0.59516 1.472e-15
## Proportion of Variance 0.6376 0.1610 0.1165 0.06519 0.01968 0.000e+00
## Cumulative Proportion 0.6376 0.7987 0.9151 0.98032 1.00000 1.000e+00
#Vectores de carga
PCs$rotation
## PC1 PC2 PC3 PC4 PC5
## PF 0.28318139 0.05873979 -0.12676408 -0.0986834614 -0.26286954
## PS 0.29198342 -0.04553725 -0.04987881 0.0919911890 0.03050520
## NH 0.28615525 -0.03980155 -0.08689315 0.1648887118 -0.14872426
## NFM 0.28615525 -0.03980155 -0.08689315 0.1648887118 -0.14872426
## NFH 0.28901048 0.05067490 0.01157256 0.1071653735 0.23827328
## AF 0.28792399 -0.04790649 -0.02250700 0.1720928839 0.13056596
## PHOTO 0.24789845 -0.16754462 -0.31886112 -0.0003973931 -0.02070010
## TRAN 0.29291281 0.03523919 0.07036698 0.0219668271 0.04446957
## UEAF -0.22561904 -0.24249812 -0.32673360 0.0446479601 0.23260831
## ATFL -0.18194252 -0.41765368 -0.05339944 0.2364973502 -0.34792888
## ATF 0.04348250 0.42175951 -0.13199115 0.5883847209 0.23748960
## ATFR -0.04888228 0.07471890 -0.65286595 -0.0822027898 -0.39367048
## ORP -0.18748635 -0.14101628 0.03425344 0.6713626458 -0.14601578
## SST 0.06521129 -0.40909876 0.45554309 0.1174575474 -0.20499374
## NFTO 0.18389610 -0.41587883 -0.09763338 -0.0525287428 0.49659489
## PFTO 0.23855494 -0.33821638 -0.05974657 -0.0747486886 -0.05936707
## COND 0.29474188 0.01177051 -0.01629098 -0.0018224501 -0.07415180
## CI 0.22763040 0.25631290 0.28940566 -0.0456858181 -0.32247823
## PC6
## PF 0.029567522
## PS -0.013159139
## NH -0.108680842
## NFM -0.042585007
## NFH 0.006527531
## AF -0.135420913
## PHOTO 0.533232079
## TRAN -0.052429021
## UEAF -0.415957108
## ATFL -0.065992367
## ATF -0.088320729
## ATFR -0.256369640
## ORP 0.128723152
## SST -0.074667401
## NFTO -0.297251075
## PFTO -0.009366363
## COND 0.177458363
## CI -0.535609356
#Despliegue los primeros renglones de los vectores de récords
head(PCs$x)
## PC1 PC2 PC3 PC4 PC5 PC6
## [1,] -3.6190255 1.2552869 -0.9560325 1.4871570 -0.23891653 1.720846e-15
## [2,] -4.7841355 -0.5777816 0.5218172 -1.4988092 -0.06803188 1.776357e-15
## [3,] 1.6069387 -1.8638845 1.8821433 0.8453614 -0.39669531 1.221245e-15
## [4,] 3.4588217 -0.2366063 -1.8386832 -0.7051859 -0.61524100 1.193490e-15
## [5,] 2.4711510 2.7164261 1.2668910 -0.3716397 0.26971873 1.443290e-15
## [6,] 0.8662495 -1.2934406 -0.8761358 0.2431163 1.04916599 1.332268e-15
#Grafica con los porcentajes de varianzas explicadas para los componentes
PCs_var <- PCs$sdev^2
porc_var <- PCs_var/(sum(PCs_var))
plot(porc_var,main="%de varianzas",col="salmon4", xlab="PC's",ylab="% varianzas PC's",type="b",lwd=2)
porc_var_acum <- cumsum(porc_var)
#Grafica con los porcentajes acumulados de varianzas explicadas
porc_var_acum <- cumsum(porc_var)
plot(porc_var_acum,main="% acumulados de Varianzas",col="tomato4",xlab="PC's",ylab="% varianzas PC's",type="b",lwd=2)
# Construccion del biplot
biplot (PCs, col=c("black","blue"), xlab="PC1 (63.76 %)",ylab="PC2 (16.10 %)", xlim=c(-0.70,0.65) )
abline(h=0, v=0 , col="black",cex= c(1,.7))
#Score
scores <- PCs$x
scores
## PC1 PC2 PC3 PC4 PC5 PC6
## [1,] -3.6190255 1.2552869 -0.9560325 1.4871570 -0.23891653 1.720846e-15
## [2,] -4.7841355 -0.5777816 0.5218172 -1.4988092 -0.06803188 1.776357e-15
## [3,] 1.6069387 -1.8638845 1.8821433 0.8453614 -0.39669531 1.221245e-15
## [4,] 3.4588217 -0.2366063 -1.8386832 -0.7051859 -0.61524100 1.193490e-15
## [5,] 2.4711510 2.7164261 1.2668910 -0.3716397 0.26971873 1.443290e-15
## [6,] 0.8662495 -1.2934406 -0.8761358 0.2431163 1.04916599 1.332268e-15
#Cluster Dendograma
#Prepare hierarchical cluster
score.cp <- read.delim("~/CONGRESO/Articulos INIFAP/score cp.txt")
data <- score.cp
attach(data)
## The following object is masked from data (pos = 3):
##
## Trat
di <- dist(data[-1], method="euclidean")
tree <- hclust(di, method="ward.D2")
data$hcluster <- as.factor((cutree(tree, k=3)-2) %% 3 +1)
# Agrupaccion de los hermanos mas proximos
plot(tree, xlab="")
rect.hclust(tree, k=3, border="red")
Fin del analisis de componentes principales, correlacion y cluster