Ranks of Data
Returns a vector of the (mid-) ranks of the input.
mu.rank(x, na.last = TRUE, na.rm=Inf) mu.rank.nna(x)
x |
numeric vector. Missing values ( |
na.last |
vector with one element.
If |
na.rm |
logical flag, indicating if missing values ( |
mu.rank is faster than rank. The treatment of missing
values is controlled by both na.last and na.rm.
the ranks; i.e., the i-th value is the rank of x[i].
In case of ties, average ranks is returned.
Knut M. Wittkowski kmw@rockefeller.edu, Tingting Song ttsong@gmail.com
a <- c(4, 2, 5, 1, 4, NA, 6)
mu.rank(a) # default: na.last=TRUE, na.rm=FALSE
# [1] 3.5 2.0 5.0 1.0 3.5 7.0 6.0
mu.rank(a,na.last=NA) # default: na.rm=TRUE
# [1] 3.5 2.0 5.0 1.0 3.5 6.0
mu.rank(a,na.last=NA,na.rm=FALSE)
# 3.5 2.0 5.0 1.0 3.5 NA 6.0
# Spearman's rank correlation between two sets of testscores
a <- c(4, 2, 5, 1, 4, NA, 6)
b <- c(4, 2, 5, NA, 4, 5, 6)
cor(a, b, if(is.R()) "complete.obs" else "available")
# [1] 0.8241688
cor(a, b, if(is.R()) "pairwise.complete.obs" else "omit")
# [1] 1
cor(rank(a), rank(b))
# [1] 0.1651446
cor(mu.rank(a, na.last=NA, na.rm=FALSE),
mu.rank(b, na.last=NA, na.rm=FALSE),
if(is.R()) "complete.obs" else "available")
# [1] 0.8523852
cor(mu.rank(a, na.last=NA, na.rm=FALSE),
mu.rank(b, na.last=NA, na.rm=FALSE),
if(is.R()) "pairwise.complete.obs" else "omit")
# [1] 0.9953452
cor(rank(a[!is.na(a*b)]), rank(b[!is.na(a*b)]))
# [1] 1Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.