问题描述
假设我有一个 n × 2 矩阵和一个将 2 向量作为其参数之一的函数.我想将该函数应用于矩阵的每一行并获得一个 n 向量.如何在 R 中做到这一点?
Suppose I have a n by 2 matrix and a function that takes a 2-vector as one of its arguments. I would like to apply the function to each row of the matrix and get a n-vector. How to do this in R?
例如,我想计算三个点上的二维标准正态分布的密度:
For example, I would like to compute the density of a 2D standard Normal distribution on three points:
bivariate.density(x = c(0, 0), mu = c(0, 0), sigma = c(1, 1), rho = 0){
exp(-1/(2*(1-rho^2))*(x[1]^2/sigma[1]^2+x[2]^2/sigma[2]^2-2*rho*x[1]*x[2]/(sigma[1]*sigma[2]))) * 1/(2*pi*sigma[1]*sigma[2]*sqrt(1-rho^2))
}
out <- rbind(c(1, 2), c(3, 4), c(5, 6))
如何将函数应用到out
的每一行?
How to apply the function to each row of out
?
如何以您指定的方式将除指向函数之外的其他参数的值传递给函数?
How to pass values for the other arguments besides the points to the function in the way you specify?
推荐答案
您只需使用 apply()
函数:
R> M <- matrix(1:6, nrow=3, byrow=TRUE)
R> M
[,1] [,2]
[1,] 1 2
[2,] 3 4
[3,] 5 6
R> apply(M, 1, function(x) 2*x[1]+x[2])
[1] 4 10 16
R>
这需要一个矩阵并对每一行应用一个(愚蠢的)函数.您将额外的参数作为第四个、第五个、...参数传递给 apply()
.
This takes a matrix and applies a (silly) function to each row. You pass extra arguments to the function as fourth, fifth, ... arguments to apply()
.
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