3

私は一般的にRと統計に非常に慣れておらず、複数の信頼楕円をPCAプロットに追加するのに苦労しています。

私の関心は、PCA プロットで潜在的なグループ化/クラスターを 95% 信頼楕円で強調表示することです。R で dataEllipse 関数を使用してみましたが、中心が異なる複数の楕円を PCA プロットに追加する方法がわかりません (中心は、クラスターを含むように見えるさまざまなポイントにあります。この場合、石のソースと石のツール)そのソースから作られている可能性があります）。

これについて助けてくれてありがとう！{

lithic_final <- LITHIC.DATASHEET.FOR.R.COMPLETE.FORMAT
lithic_final

pca1 <- princomp(lithic_final); pca1

lithic_source <- c("A1", "A1", "A1", "A1", "A2","A2", "A2", "A3","A3","A3","B","B","B","B","B","B","C","C","C","C","C","C","C","D","D","D","D","D","D","D","D","E","E","E","E","E","E","E","E","F","F","G","G","G","G","H","H","H","H","H","H","H","I1","I1","I1","I2","I2","I2","I2","I2","J1","J1","J2","J2","J2","J2","J2","J2","J2","J2","J2","K","K","K","K","K","K","K","L","L","L","L","L","L","L","L","L","L","L","L","L","L","BB1","BB1","BB1","FC","FC","FC","JRPP","JRPP","JRPP","BB2","BB2","BB2","BB2","MWP","MWP","MWP","MWP","RPO","RPO","RPO")

lithic_source

summary(pca1)

plot(pca1)

#Plotting the scores with the Lithic Source Info
round(pca1$scores[,1:2], 2)
pca_scores <-round(pca1$scores[,1:2], 2)
plot(pca1$scores[,1], pca1$scores[,2], type="n")
text(pca1$scores[,1], pca1$scores[,2],labels=abbreviate(lithic_source, minlength=3), cex=.45)



#Plotting PCA Scores of EACH SAMPLE for PCA 2 and 3 with Lithic Source Info
round(pca1$scores[,2:3], 2)
pca2_3_scores <-round(pca1$scores[,2:3], 2)
plot(pca1$scores[,2], pca1$scores[,3], type="n")
text(pca1$scores[,2], pca1$scores[,3], labels=abbreviate(lithic_source, minlength=3), cex=.45)

#Plotting PCA Scores of EACH SAMPLE for PCA 3 and 4 with Lithic Source Info
round(pca1$scores[,3:4], 2)
pca3_4_scores <-round(pca1$scores[,3:4], 2)
plot(pca1$scores[,3], pca1$scores[,4], type="n")
text(pca1$scores[,3], pca1$scores[,4], labels=abbreviate(lithic_source, minlength=3), cex=.45)

#Plotting PCA Scores of EACH SAMPLE for PCA 1 and 3 with Lithic Source Info
round(pca1$scores[,1:3], 2)
pca1_3_scores <-round(pca1$scores[,1:3], 2)
plot(pca1$scores[,1], pca1$scores[,3], type="n")
text(pca1$scores[,1], pca1$scores[,3], labels=abbreviate(lithic_source, minlength=3), cex=.45)

#Plotting PCA Scores of EACH SAMPLE for PCA 1 and 4 with Lithic Source Info
round(pca1$scores[,1:4], 2)
pca1_4_scores <-round(pca1$scores[,1:4], 2)
plot(pca1$scores[,1], pca1$scores[,4], type="n")
text(pca1$scores[,1], pca1$scores[,4], labels=abbreviate(lithic_source, minlength=3), cex=.45)

#TRYING TO GET ELLIPSES ADDED TO PCA 1 and 4 scores
dataEllipse(pca1$scores[,1], pca1$scores[,4],centers=12,add=TRUE,levels=0.9, plot.points=FALSE)


structure(list(Ca.K12 = c(418L, 392L, 341L, 251L, 297L, 238L, 
258L, 5L, 2L, 37L), Cr.K12 = c(1L, 12L, 15L, 6L, 9L, 6L, 35L, 
7L, 45L, 32L), Cu.K12 = c(89L, 96L, 81L, 63L, 88L, 103L, 104L, 
118L, 121L, 90L), Fe.K12 = c(18627L, 18849L, 18413L, 12893L, 
17757L, 17270L, 16198L, 2750L, 4026L, 3373L), K.K12 = c(20L, 
23L, 28L, 0L, 34L, 17L, 45L, 102L, 150L, 147L), Mn.K12 = c(205L, 
212L, 235L, 120L, 216L, 212L, 246L, 121L, 155L, 115L), Nb.K12 = c(139L, 
119L, 154L, 91L, 122L, 137L, 137L, 428L, 414L, 428L), Rb.K12 = c(99L, 
42L, 79L, 49L, 210L, 243L, 168L, 689L, 767L, 705L), Sr.K12 = c(3509L, 
3766L, 3481L, 2715L, 2851L, 2668L, 2695L, 202L, 220L, 217L), 
    Ti.K12 = c(444L, 520L, 431L, 293L, 542L, 622L, 531L, 82L, 
    129L, 84L), Y.K12 = c(135L, 121L, 105L, 74L, 144L, 79L, 85L, 
    301L, 326L, 379L), Zn.K12 = c(131L, 133L, 108L, 78L, 124L, 
    111L, 114L, 81L, 78L, 59L), Zr.K12 = c(1348L, 1479L, 1333L, 
    964L, 1506L, 1257L, 1296L, 3967L, 4697L, 4427L)), .Names = c("Ca.K12", 
"Cr.K12", "Cu.K12", "Fe.K12", "K.K12", "Mn.K12", "Nb.K12", "Rb.K12", 
"Sr.K12", "Ti.K12", "Y.K12", "Zn.K12", "Zr.K12"), row.names = c(NA, 
10L), class = "data.frame")
4

2 に答える 2

6

余計なことではなく質問に集中していれば、もっと迅速な回答が得られたと思います。あなたの質問とは関係のない一連の主成分をプロットするためのコマンドを私たちに与えました。問題は、グループごとに楕円をどのようにプロットするかです。データ楕円をプロットするには 3 点では不十分なため、10 行と 3 つのグループのサンプル データは役に立ちません。あなたの質問に対する最も簡単な答えを持っているパッケージ car で dataEllipse 関数を使用しています:

まず、再現可能な例:

set.seed(42) # so you can get the same numbers I get
source_a <- data.frame(X1=rnorm(25, 50, 5), X2=rnorm(25, 40, 5))
source_b <- data.frame(X1=rnorm(25, 20, 5), X2=rnorm(25, 40, 5))
source_c <- data.frame(X1=rnorm(25, 35, 5), X2=rnorm(25, 25, 5))
lithic_dat <- rbind(source_a, source_b, source_c)
lithic_source <- c(rep("a", 25), rep("b", 25), rep("c", 25))

scatterplot() で楕円をプロットし、テキストを追加します。

scatterplot(X2~X1 | lithic_source, data=lithic_dat, pch="", smooth=FALSE, 
     reg.line=FALSE, ellipse=TRUE, levels=.9)
text(lithic_dat$X1, lithic_dat$X2, lithic_source, cex=.75)

Scatterplot を微調整して、必要なすべてのことを行うことができますが、それを使用せずに楕円をプロットすることもできます。

sources <- unique(lithic_source) # vector of the different sources
plot(lithic_dat$X1, lithic_dat$X1, type="n")
text(lithic_dat$X1, lithic_dat$X2, lithic_source, cex=.75)
for (i in sources) with(lithic_dat, dataEllipse(X1[lithic_source==i],
     X2[lithic_source==i], levels=.9, plot.points=FALSE))

これは、主成分およびその他のデータに対して機能します。

于 2012-08-23T16:50:47.220 に答える
3

ggbiplot (github で入手可能) と呼ばれるパッケージをアイリス データと共に使用する簡単なソリューションを次に示します。これがあなたが探していたものであることを願っています。

library(devtools);install_github('vqv/ggbiplot')
library(ggbiplot)
pca = prcomp(iris[,1:4]) 
ggbiplot(pca,groups = iris$Species,ellipse = T,ellipse.prob = .95)
于 2016-05-24T03:37:32.923 に答える