R：矩阵乘法错误（不一致的参数）
R: Errors in Matrix Multiplication (non-conformable arguments)
我正在使用 R 编程语言。
我有以下数据：
1) 均值向量（4 行，1 列）
4 个变量（x1、x2、x3、x4）
5.0060022
3.4280049
1.4620007
0.2459998
2）协方差矩阵（4行，4列）
4 个变量（对角线元素是 x1、x2、x3、x4，成对元素是例如第二个元素：(x1,x2)、第三个元素 (x1,x3)、第四个元素 (x1, x4) 等）
0.15065114 0.13080115 0.02084463 0.01309107
0.13080115 0.17604529 0.01603245 0.01221458
0.02084463 0.01603245 0.02808260 0.00601568
0.01309107 0.01221458 0.00601568 0.01042365
问题：我想获取上述数据并在以下格式：
这是我到目前为止尝试过的：
my_function <- function(x_one, x_two, x_three, x_four)
{
sigma1.pre <- c(0.15065114 , 0.13080115 , 0.02084463 , 0.01309107 , 0.13080115 , 0.17604529 , 0.01603245 , 0.01221458 , 0.02084463 , 0.01603245 , 0.02808260 , 0.00601568 , 0.01309107 , 0.01221458 , 0.00601568 , 0.01042365)
sigma1 <- matrix(sigma1.pre, nrow=4, ncol= 4, byrow = TRUE)
sigma1_inv <- ginv(sigma1)
det_sigma1_inv <- det(sigma1_inv)
denom = sqrt( (2*pi)^4 * det_sigma1_inv)
x_one = x1 - 5
x_two = x2 - 3.42
x_three = x3 - 1.462
x_four = x4 - 0.245
x_t = c(x_one, x_two, x_three, x_four)
x_t_one <- matrix(x_t, nrow=4, ncol= 1, byrow = TRUE)
x_t_one_t = -0.5 * t(x_t_one)
x_t_two = matrix(x_t, nrow=1, ncol= 4, byrow = TRUE)
num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t)
answer = num/denom
return(answer)
}
问题：当我尝试运行这个函数时：
my_function(1,2,3,4)
我收到以下错误：
Error in x_t_two %*% sigma1_inv %*% x_t_one_t : non-conformable arguments
我认为错误是由于矩阵乘法引起的
num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t)
我尝试更改矩阵乘法的顺序：
num = exp( x_t_one_t %*% sigma1_inv %*% x_t_two )
但错误依然存在。
有人可以告诉我如何解决这个问题吗？
谢谢！
参考文献：
正如我上面提到的，dmvnorm函数returns你显示的函数的值。
dmvnorm(c(5,3,1,0),m,v)
[1] 0.01074766
这是我的手动版本，
func <- function(vec, m, v){
if (length(vec) != length(m)) {
stop("dimension error")
} # and several more
a <- t(vec - m) %*% solve(v) %*% (vec - m)
k <- length(vec)
return(exp(-a/2)/sqrt((2*pi)^k * det(v)))
}
func(c(5,3,1,0) , m, v)
[,1]
[1,] 0.01074766
在您的函数中，您的函数不起作用的主要原因是第 num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t) 行，x_t_one_t 的维数错误。当您将其设置为 nrow = 4, ncol = 1 时，它已经是 4*1，您不需要转置它。我对你的函数添加了一些评论。
my_function <- function(x_one, x_two, x_three, x_four)
{
sigma1.pre <- c(0.15065114 , 0.13080115 , 0.02084463 , 0.01309107 , 0.13080115 , 0.17604529 , 0.01603245 , 0.01221458 , 0.02084463 , 0.01603245 , 0.02808260 , 0.00601568 , 0.01309107 , 0.01221458 , 0.00601568 , 0.01042365)
sigma1 <- matrix(sigma1.pre, nrow=4, ncol= 4, byrow = TRUE)
# You can also use solve instead of ginv, solve is in base R
sigma1_inv <- ginv(sigma1)
det_sigma1_inv <- det(sigma1_inv)
# In here, not det_sigma1_inv, just use det(sigma1) will work.
denom = sqrt( (2*pi)^4 * det(sigma1))
#in below part, I recommend another way.
#m <- c( 5.0060022, 3.4280049, 1.4620007, 0.2459998)
#x_t = c(x_one, x_two, x_three, x_four)
#There was no input x1, x2, x3, x4
x_one = x_one - 5.0060022
x_two = x_two - 3.4280049
x_three = x_three - 1.4620007
x_four = x_four - 0.2459998
# Vectors and matrices are handle as vector and matrices. You do not need to
#change vectors to matrices.
#x_t_t = x_t - m
x_t = c(x_one, x_two, x_three, x_four)
x_t_one <- matrix(x_t, nrow=4, ncol= 1, byrow = TRUE)
x_t_two = matrix(x_t, nrow=1, ncol= 4, byrow = TRUE)
# In this part, as it's (x-mu)^T * SIGMA * (x-mu), dimension of x_t_one_t was wrong
# You may try another way.
#num = exp(-0.5 * t(x_t_t) %*% sigma1_inv %*% x_t_t)
num = exp(-0.5 * x_t_two %*% sigma1_inv %*% x_t)
answer = num/denom
return(answer)
}
my_function(5,3,1,0)
[,1]
[1,] 0.01074766
我正在使用 R 编程语言。
我有以下数据：
1) 均值向量（4 行，1 列）
4 个变量（x1、x2、x3、x4）
5.0060022
3.4280049
1.4620007
0.2459998
2）协方差矩阵（4行，4列）
4 个变量（对角线元素是 x1、x2、x3、x4，成对元素是例如第二个元素：(x1,x2)、第三个元素 (x1,x3)、第四个元素 (x1, x4) 等）
0.15065114 0.13080115 0.02084463 0.01309107
0.13080115 0.17604529 0.01603245 0.01221458
0.02084463 0.01603245 0.02808260 0.00601568
0.01309107 0.01221458 0.00601568 0.01042365
问题：我想获取上述数据并在以下格式：
这是我到目前为止尝试过的：
my_function <- function(x_one, x_two, x_three, x_four)
{
sigma1.pre <- c(0.15065114 , 0.13080115 , 0.02084463 , 0.01309107 , 0.13080115 , 0.17604529 , 0.01603245 , 0.01221458 , 0.02084463 , 0.01603245 , 0.02808260 , 0.00601568 , 0.01309107 , 0.01221458 , 0.00601568 , 0.01042365)
sigma1 <- matrix(sigma1.pre, nrow=4, ncol= 4, byrow = TRUE)
sigma1_inv <- ginv(sigma1)
det_sigma1_inv <- det(sigma1_inv)
denom = sqrt( (2*pi)^4 * det_sigma1_inv)
x_one = x1 - 5
x_two = x2 - 3.42
x_three = x3 - 1.462
x_four = x4 - 0.245
x_t = c(x_one, x_two, x_three, x_four)
x_t_one <- matrix(x_t, nrow=4, ncol= 1, byrow = TRUE)
x_t_one_t = -0.5 * t(x_t_one)
x_t_two = matrix(x_t, nrow=1, ncol= 4, byrow = TRUE)
num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t)
answer = num/denom
return(answer)
}
问题：当我尝试运行这个函数时：
my_function(1,2,3,4)
我收到以下错误：
Error in x_t_two %*% sigma1_inv %*% x_t_one_t : non-conformable arguments
我认为错误是由于矩阵乘法引起的
num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t)
我尝试更改矩阵乘法的顺序：
num = exp( x_t_one_t %*% sigma1_inv %*% x_t_two )
但错误依然存在。
有人可以告诉我如何解决这个问题吗？
谢谢！
参考文献：
正如我上面提到的，dmvnorm函数returns你显示的函数的值。
dmvnorm(c(5,3,1,0),m,v)
[1] 0.01074766
这是我的手动版本，
func <- function(vec, m, v){
if (length(vec) != length(m)) {
stop("dimension error")
} # and several more
a <- t(vec - m) %*% solve(v) %*% (vec - m)
k <- length(vec)
return(exp(-a/2)/sqrt((2*pi)^k * det(v)))
}
func(c(5,3,1,0) , m, v)
[,1]
[1,] 0.01074766
在您的函数中，您的函数不起作用的主要原因是第 num = exp(x_t_two %*% sigma1_inv %*% x_t_one_t) 行，x_t_one_t 的维数错误。当您将其设置为 nrow = 4, ncol = 1 时，它已经是 4*1，您不需要转置它。我对你的函数添加了一些评论。
my_function <- function(x_one, x_two, x_three, x_four)
{
sigma1.pre <- c(0.15065114 , 0.13080115 , 0.02084463 , 0.01309107 , 0.13080115 , 0.17604529 , 0.01603245 , 0.01221458 , 0.02084463 , 0.01603245 , 0.02808260 , 0.00601568 , 0.01309107 , 0.01221458 , 0.00601568 , 0.01042365)
sigma1 <- matrix(sigma1.pre, nrow=4, ncol= 4, byrow = TRUE)
# You can also use solve instead of ginv, solve is in base R
sigma1_inv <- ginv(sigma1)
det_sigma1_inv <- det(sigma1_inv)
# In here, not det_sigma1_inv, just use det(sigma1) will work.
denom = sqrt( (2*pi)^4 * det(sigma1))
#in below part, I recommend another way.
#m <- c( 5.0060022, 3.4280049, 1.4620007, 0.2459998)
#x_t = c(x_one, x_two, x_three, x_four)
#There was no input x1, x2, x3, x4
x_one = x_one - 5.0060022
x_two = x_two - 3.4280049
x_three = x_three - 1.4620007
x_four = x_four - 0.2459998
# Vectors and matrices are handle as vector and matrices. You do not need to
#change vectors to matrices.
#x_t_t = x_t - m
x_t = c(x_one, x_two, x_three, x_four)
x_t_one <- matrix(x_t, nrow=4, ncol= 1, byrow = TRUE)
x_t_two = matrix(x_t, nrow=1, ncol= 4, byrow = TRUE)
# In this part, as it's (x-mu)^T * SIGMA * (x-mu), dimension of x_t_one_t was wrong
# You may try another way.
#num = exp(-0.5 * t(x_t_t) %*% sigma1_inv %*% x_t_t)
num = exp(-0.5 * x_t_two %*% sigma1_inv %*% x_t)
answer = num/denom
return(answer)
}
my_function(5,3,1,0)
[,1]
[1,] 0.01074766