R循环-添加没有预定义尺寸的行 [英] R Loop - Adding rows without predefined dimensions

问题描述

我想将测试结果存储在矩阵或data.frame中的R for循环内，该矩阵或data.frame具有(在这种情况下)两列，但行数不确定，因为行数取决于if语句.

I want to store the results of a test within an R for loop inside a matrix or data.frame with (in this case) two columns, but an indeterminate number of rows, because the number of rows will depend on an if statement.

我正在比较一周中几天的计数，然后进行成对比较.这是现在的代码:

I am comparing counts for days of the week, and then doing pairwise comparisons. This is the code as it stands now:

week <- c(Mon = 401, Tue = 199, Wed = 187, Thur = 202, Fri = 240, Sat = 212, Sun = 244)
names(week) <- NULL
observed <- week


for(i in 1:(length(observed) - 1)){
  for(j in 1:(length(observed))){
    test <- chisq.test(c(observed[i], observed[j]), p = rep(1/2, 2))
    if(test$p.value < 0.002380952) print(c(i,j)) 
  }
}

现在输出为:

[1] 1 2
[1] 1 3
[1] 1 4
[1] 1 5
[1] 1 6
[1] 1 7
[1] 2 1
[1] 3 1
[1] 4 1
[1] 5 1
[1] 6 1

但是根据函数中if语句的结果，它可能更长.此外，我最终希望消除排列.

But depending on the results of the if statement in the function, it could have been much longer. Further I want to ultimately erase permutations.

寻找在循环中初始化空矩阵(或data.frame)的方法，它们似乎提前合并了维度，例如在days <- matrix(NA, nrow = length(observed)^2, ncol = 2)中.

Looking for ways to initiate an empty matrix (or data.frame) in the loop, they seem to incorporate the dimensions ahead of time, such as in days <- matrix(NA, nrow = length(observed)^2, ncol = 2).

相反，我希望行数不确定.

I'd like to, instead, have an indeterminate number of rows.

推荐答案

这有效:

mat <- combn(1:length(observed),2)
vec <- apply(mat, 2, function(x) chisq.test(observed[x],p=rep(1/2,2))$p.value)
mat[,c(vec < 0.002380952)] 

#     [,1] [,2] [,3] [,4] [,5] [,6]
#[1,]    1    1    1    1    1    1
#[2,]    2    3    4    5    6    7

说明: combn查找数字之间的所有组合，并将它们作为矩阵返回(2行乘n列).然后，我们遍历n列并找到p值.然后，我们为小于子阈值的vec元素子集mat.

Explanation: combn finds all combinations between numbers and returns them as a matrix (2 rows by n columns). Then we go over the n columns and find the p-values. We then subset mat for the elements of vec that are smaller than your threshold.

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