以下代码可用于创建一个数据框架,其中Kendall-Tau和Spearman相关结果彼此相邻:
data(mtcars)
mtcars
correlation <- function(x,y){
df1 = cor(data.frame(x,y), use="complete.obs", method="kendall")
df2 = cor(data.frame(x,y), use="complete.obs", method="spearman")
return(data.frame(df1,df2))
}
correlation(mtcars[1],mtcars[2])
问题:不是将命令链接起来,而是可以实现两种方法的循环吗?
methods <- ("kendall", "spearman")
correlation <- function(x,y){
df = cor(data.frame(x,y), use="complete.obs", method=methods)
return(data.frame(df))
}
correlation(mtcars[1],mtcars[2])
#This should output the two results, just as above.
我尝试了一个列表,但没有成功。
答案 0 :(得分:0)
# vector that has your methods
methods <- c("kendall", "spearman")
# function which loops thru the vector of functions
correlation <- function(x,y) {
a <- lapply(X = methods, FUN = function(m,x,y){
df1 = cor(data.frame(x,y), use="complete.obs", method= m)
},x=x,y=y)
return(a)
}
res <- correlation(mtcars[1],mtcars[2])
#list to dataframe
do.call("cbind", lapply(res, as.data.frame))
结果:
mpg cyl mpg cyl
mpg 1.0000000 -0.7953134 1.0000000 -0.9108013
cyl -0.7953134 1.0000000 -0.9108013 1.0000000
谢谢!