在我的数据集中,我必须按组执行相关
我写
require(plyr)
func <- function(terr)
{
return(data.frame(COR = cor(terr$Killed, terr$Terr..Attacks,terr$GDP.capita)))
}
ddply(terr, .(Macro.Region,Religion), func)
然后我收到了错误
Error in cor(terr$Killed, terr$Terr..Attacks, terr$GDP.capita) :
invalid 'use' argument
出了什么问题,如何纠正执行分析
terr=structure(list(Macro.Region = structure(c(5L, 4L, 4L, 3L, 4L,
6L, 1L, 2L, 4L, 3L, 6L, 5L, 4L, 4L, 3L, 4L, 6L, 1L, 2L, 4L, 3L,
6L), .Label = c("Arab Countries", "Asia", "Eastern Europe and post-Soviet",
"Latin America", "Sub-Saharan Africa", "Western States"), class = "factor"),
Killed = c(0L, 0L, 0L, 6L, 0L, 0L, 1L, 76L, 0L, 0L, 36L,
0L, 0L, 0L, 6L, 0L, 0L, 1L, 76L, 0L, 0L, 36L), Terr..Attacks = c(2L,
0L, 2L, 2L, 0L, 9L, 3L, 88L, 0L, 0L, 6L, 2L, 0L, 2L, 2L,
0L, 9L, 3L, 88L, 0L, 0L, 6L), Religion = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L), .Label = c("Christianity", "Islam"
), class = "factor"), GDP.capita = c(6813L, 26198L, 20677L,
9098L, NA, 49882L, 51846L, 4207L, 17508L, 18616L, 46301L,
6813L, 26198L, 20677L, 9098L, NA, 49882L, 51846L, 4207L,
17508L, 18616L, 46301L)), class = "data.frame", row.names = c(NA,
-22L))
这里的解决方案spearman correlation by group in R不合适,因为我有两个小组和三个大战
答案 0 :(得分:1)
您可以尝试tidyverse
使用purrr
函数keep
来限制具有足够样本大小的组和map
来计算成对相关性。
library(tidyverse)
terr %>%
split(list(.$Macro.Region, .$Religion)) %>%
keep(~nrow(.) > 3) %>%
map(~.x %>%
select(Killed,GDP.capita,Terr..Attacks) %>%
cor(cbind.data.frame(.), use = "complete.obs"))
$`Eastern Europe and post-Soviet.Christianity`
Killed GDP.capita Terr..Attacks
Killed 1 -1 1
GDP.capita -1 1 -1
Terr..Attacks 1 -1 1
$`Latin America.Christianity`
Killed GDP.capita Terr..Attacks
Killed NA NA NA
GDP.capita NA 1.0000000 -0.1543897
Terr..Attacks NA -0.1543897 1.0000000
$`Western States.Christianity`
Killed GDP.capita Terr..Attacks
Killed 1 -1 -1
GDP.capita -1 1 1
Terr..Attacks -1 1 1
尝试Hmisc
的{{1}}函数来检索相应的pvalues
rcorr