第1个回答 2016-06-04
#####以10个数据和30个数据为例说明。####
my.qqplot <- function(y){
op <- par(mfrow = c(1, 1))
N <- length(y)
n <- seq(1, N)
xais <- qnorm((n - (.5*N) /N)/ N)
#####中间三句可选，只是为了输出计算过程######
mid <- cbind(sort(y), n, n/N, (n-(.5*N)/N)/N , xais)
colnames(mid) <- c("y", "rank", "cumpercent", "adj-cumper","xaix")
print(mid)
#####中间三句可选，只是为了输出计算过程######
par(mfrow = c(2,1))
qqnorm(y)
plot(sort(y) ~ xais, main = 'my qqplot')
par(op)
}
y <- rnorm(10, mean = 20, s = 50)
my.qqplot(y)
y rank cumpercentadj-cumper xaix
[1,] 2.877321 1 0.1 0.05 -1.6448536
[2,] 6.930063 2 0.2 0.15 -1.0364334
[3,] 16.461444 3 0.3 0.25 -0.6744898
[4,] 36.130825 4 0.4 0.35 -0.3853205
[5,] 40.477883 5 0.5 0.45 -0.1256613
[6,] 50.534636 6 0.6 0.55 0.1256613
[7,] 53.425025 7 0.7 0.65 0.3853205
[8,] 54.554269 8 0.8 0.75 0.6744898
[9,]120.496268 9 0.9 0.85 1.0364334
[10,] 125.290253 10 1.0 0.95 1.6448536本回答被网友采纳