Hi,
I know what the following correlation methods ("pearson", "kendall",
"spearman") are through wiki. But I'm wondering if there is a good
book that discuss why these metrics are defined and when to use one
coefficient versus the others.
cor.test(x, y,
alternative = c("two.sided", "less", "greater"),
method = c("pearson", "kendall", "spearman"),
exact = NULL, conf.level = 0.95, ...)
cov(x, y = NULL, use = "everything",
method = c("pearson", "kendall", "spearman"))
cor(x, y = NULL, use = "everything",
method = c("pearson", "kendall", "spearman"))
I know that "cor(x,y)=cov(x,y)/sqrt(var(x)*var(y))". What is the
relation between cor(), cov(), cor.test() for "kendall" and
"spearman"?
Regards,
Peng
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
