> rank(t <- c(6.8, 8.1, 7.2))
[1] 1 3 2

> rank(-(s <- c(74, 92, 85)))
[1] 3 1 2

> t <- c(4, NaN, 4, 7, 8, 2, NaN, 9, 9, 7, NaN, 5, 2, 2, 1)
#同时对相应元素做好标记
> names(t) <- letters[1 : length(t)]

function (x, na.last = TRUE, ties.method = c("average", "first", "random", "max", "min"))
{nas <- is.na(x) #得到与x相同长度的boolean型数组，用来标记相应位是否为缺失值nm <- names(x)  #获取数组中元素所对应的标签　　#names函数暗示了该方法的设计初衷是对一维数组即列向量进行排序，虽然x为矩阵也会得出结果，但nm的作用已经失效，结果不具有意义　　ties.method <- match.arg(ties.method)if (is.factor(x)) x <- as.integer(x) #若x为因子，则对元素"归类"，并按"类的大小"进行整数元素编码，具体请见[说明1]x <- x[!nas] #剔除x中的缺失值

　　#average\min\max采用了相应的.Internal(rank(x, length(x), ties.method))，具体请见[说明2]　　#first采用了sort.list(sort.list(x))，具体请见[说明3]　　#random采用了sort.list(order(x, stats::runif(sum(!nas))))，具体请见[说明4]y <- switch(ties.method, average = , min = , max = .Internal(rank(x, length(x), ties.method)), first = sort.list(sort.list(x)), random = sort.list(order(x, stats::runif(sum(!nas)))))

　　#下面是补全缺失值的次序的方法　　#na.last = "keep",不处理缺失值，na.last = TRUE,后排序缺失值，na.last = FALSE,先排序缺失值。if (!is.na(na.last) && any(nas)) {yy <- NANAkeep <- (na.last == "keep")if (NAkeep || na.last) {yy[!nas] <- yif (!NAkeep) yy[nas] <- (length(y) + 1L):length(yy)}else {len <- sum(nas)yy[!nas] <- y + lenyy[nas] <- seq_len(len)}y <- yynames(y) <- nm}else names(y) <- nm[!nas]y
}

> f <- c('Ba', 'BA', 'b', 'A', 'A', 'b', 'Ba', 'Bac', NaN, NaN)
> fac <- factor(colour)
> as.integer(fac)[1] 3 4 2 1 1 2 3 5 6 6

> qulity <- c('good','soso','good','soso','bad','good','bad')
> names(qulity) <- c('day1','day2','day3','day4','day5','day6','day7')
> q <- factor(qulity, levels = c('bad','soso','good'), labels = c('bad', 'soso', 'good'), order = TRUE)
> rank(q)
day1 day2 day3 day4 day5 day6 day7 6.0  3.5  6.0  3.5  1.5  6.0  1.5 

> ta   b   c   d   e   f   g   h   i   j   k   l   m   n   o 4 NaN   4   7   8   2 NaN   9   9   7 NaN   5   2   2   1
> rank(t, na.last = "keep", ties.method = "first")a  b  c  d  e  f  g  h  i  j  k  l  m  n  o 5 NA  6  8 10  2 NA 11 12  9 NA  7  3  4  1
> rank(t, na.last = "keep", ties.method = "average")a    b    c    d    e    f    g    h    i    j    k    l    m    n    o 5.5   NA  5.5  8.5 10.0  3.0   NA 11.5 11.5  8.5   NA  7.0  3.0  3.0  1.0 

> x
a c d e f h i j l m n o
4 4 7 8 2 9 9 7 5 2 2 1
> sort.list(sort.list(x))[1]  5  6  8 10  2 11 12  9  7  3  4  1

a c d e f h i j l m n o
4 4 7 8 2 9 9 7 5 2 2 1
> weight = c(0.45, 0.55, 0.1, 0.1, 0.1, 0.55, 0.45, 0.1, 0.1, 0.3, 0.1, 0.1);
> sort.list(order(x,weight))[1]  5  6  8 10  2 12 11  9  7  4  3  1