確定自變量之間的最高相關值，並排除與 r 中因變量的最低相關值

Question

我試圖獨立變量中識別的最高相關性的值（例如> = 0.8 | <= -0.8），然后排除具有與線性模型因變量，以避免多重最低相關值的自變量。

首先，我想確定自變量之間的最高相關性，然后排除那些與稱為EC1的第一行和第一列中的因變量相關性最低的變量

數據集，如果你想運行它

cor_26_EC<-rcorr(x=as.matrix(data_26_EM[c(4,8:length(data_26_EM))]),type="pearson")

cor_test<-(cor_26_EC$r)

> head(cor_test)
                     EC1         DEM       slope      aspect northernness   plan_curv   prof_curv convergence         twi
EC1           1.0000000 -0.68580505  0.36444948 -0.17735481   0.17735481 -0.14541592 -0.21159663 -0.10027208 -0.10220409
DEM          -0.6858051  1.00000000 -0.47325220  0.06090698  -0.06090698  0.28021257  0.34739247  0.24297883 -0.02919072
slope         0.3644495 -0.47325220  1.00000000 -0.02321129   0.02321129  0.04219001  0.01703231  0.03937512 -0.56400210
aspect       -0.1773548  0.06090698 -0.02321129  1.00000000  -1.00000000 -0.01574986 -0.01260762  0.04838931  0.02877949
northernness  0.1773548 -0.06090698  0.02321129 -1.00000000   1.00000000  0.01574986  0.01260762 -0.04838931 -0.02877949
plan_curv    -0.1454159  0.28021257  0.04219001 -0.01574986   0.01574986  1.00000000  0.59109001  0.73023077 -0.51818538

(it continues...)

Answer 1

如果我理解正確，你想要的東西是這樣的：

library("dplyr")
library("reshape2")

x <- read.delim("~/Documents/stack/EM_26.txt")
c <- cor(x)
## set diagonal to NA because we don't want autocorrelation
diag(c) <- NA
## reshape from matrix to long table
mdf <- melt(c)
## Choose max correlation for each variable
## You could also filter here by a threshold value, eg filter(abs(value) > 0.8)
max_cors <- mdf %>% group_by(Var1) %>% filter(value == max(value, na.rm = TRUE)) 
## For each max correlation, drop the one which has lower correlation with EC1
drop_variables <- apply(max_cors,
  1,
  function(row) {
    row[which.min(c(c["EC1", row[[1]]], c["EC1", row[[2]]]))]
  }
)
unique(drop_variables)
#> [1] "MS1"  "z"    "EC05"