在R中模拟样本，存储样本并计算检验统计量

我使用蒙特卡罗算法，使用反演采样生成几何分布大小为100的数据样本：

gi.cdf.geom <- function(p,u){
k <- c()
k <- ceiling(log(1-u)/log(1-p)) - 1
return(k)
}

---

gi.cdf.geom使用
replicate
。例如：

(x <- replicate(3,rgeom(10,50/239)))
      [,1] [,2] [,3]
 [1,]    5    3   12
 [2,]   15    2    3
 [3,]    5    5    0
 [4,]    4    2    1
 [5,]   13    0    8
 [6,]    0    3    0
 [7,]    3    1    6
 [8,]    0    6    2
 [9,]    0    4    4
[10,]    8    4    1

但是我怎样才能在表达式参数中放入两个表达式呢？因为我需要它每次从均匀分布中随机抽取100个样本，并使用每个样本计算函数gi.cdf.geom您可以将
runif
放入您的函数调用中：
gi.cdf.geom（p，runif（n））
。否则，可以将多个表达式放在大括号中，并用分号分隔
for(i in 1:1000){
 n=100
 p=50/239
 {
  u=runif(n)
  values <- gi.cdf.geom(p,u)
 }
 print(values)

(x <- replicate(3,rgeom(10,50/239)))
      [,1] [,2] [,3]
 [1,]    5    3   12
 [2,]   15    2    3
 [3,]    5    5    0
 [4,]    4    2    1
 [5,]   13    0    8
 [6,]    0    3    0
 [7,]    3    1    6
 [8,]    0    6    2
 [9,]    0    4    4
[10,]    8    4    1

apply(x,2,chisq.test)
[[1]]

        Chi-squared test for given probabilities

data:  newX[, i] 
X-squared = 47.566, df = 9, p-value = 3.078e-07


[[2]]

        Chi-squared test for given probabilities

data:  newX[, i] 
X-squared = 10, df = 9, p-value = 0.3505


[[3]]

        Chi-squared test for given probabilities

data:  newX[, i] 
X-squared = 37.3243, df = 9, p-value = 2.303e-05


Warning messages:
1: In FUN(newX[, i], ...) : Chi-squared approximation may be incorrect
2: In FUN(newX[, i], ...) : Chi-squared approximation may be incorrect