从 R 中的 rda 对象中提取 PC 百分比

Question

我希望将主成分百分比添加到我的图表中，但我不确定如何从 rda 对象中计算/提取这些值。

library(vegan)

all.std <- na.omit(decostand(all.data, method = "normalize"))
all.rda <- rda(all.std)

# extract info for viz
uscores.all <- data.frame(all.rda$CA$u)
uscores.all <- rownames_to_column(uscores.all,"sample.id")
uscores1.all <- inner_join(icp.metadata,uscores.all, by = "sample.id")
vscores.all <- data.frame(all.rda$CA$v)

我有样本点和矢量信息，可以为我提供包含完整数据的良好图像，但如何添加 PC1 和 PC2 的％？

> dput(all.data)
structure(list(Al.308.215 = c(1933.110774, 2124.933186, 2697.142811, 
2454.099034, 2416.374341, 2730.405337, 2846.957744, 2957.419342, 
2959.348363, 2853.258817), Al.396.152 = c(1955.47859, 2142.707892, 
2719.348431, 2475.607238, 2428.867771, 2759.503064, 2875.096669, 
2990.04952, 2988.810866, 2880.507931), Ba.233.527 = c(4.758488077, 
4.873488218, 5.496073131, 5.322604493, 5.334528828, 5.519915915, 
5.715194792, 5.774621594, 7.152332657, 7.157559445), Ba.455.404 = c(4.676267981, 
4.748689692, 5.424586334, 5.246081426, 5.233062678, 5.41001526, 
5.639145829, 5.687752522, 7.029890126, 7.058378483), Ca.183.801 = c(659.0148918, 
655.0216397, 705.7125714, 699.3610886, 685.2562524, 682.351838, 
667.2459663, 666.5119829, 451.5861085, 430.0641182), Ca.317.933 = c(663.2478342, 
660.1603433, 706.2024694, 704.5687867, 685.9959824, 687.0625639, 
670.5308695, 667.5984284, 448.1139829, 428.0179807), Fe.259.941 = c(902.8585447, 
911.2101809, 1017.666402, 1022.594904, 1048.51115, 1002.091143, 
970.8258109, 905.2628883, 997.8037721, 1046.38376), K.766.491 = c(314.1726307, 
309.757608, 389.1136882, 376.3265692, 373.4714432, 413.0336628, 
420.9373827, 437.5226928, 475.3400126, 477.8208541), Mg.285.213 = c(510.5124552, 
596.0268573, 829.8716737, 768.2083155, 744.1670151, 784.4661692, 
796.7464128, 837.234733, 684.5431608, 707.3844484), Mn.257.611 = c(15.91777975, 
15.88328987, 17.680152, 17.57143193, 18.39642397, 17.96018218, 
17.69058768, 17.24667962, 19.92596564, 20.23646264)), row.names = c("2A", 
"4A", "5A", "6A", "7A", "8A", "9A", "10A", "11A", "12A"), class = "data.frame")

Answer 1

似乎我误用了

vegan::rda

功能，并使用这个很棒的教程澄清了我的需求：

https://r.qcbs.ca/workshop10/book-en/redundancy-analysis.html