马氏性检验matlab代码
时间: 2024-02-05 11:09:06 浏览: 42
根据提供的引用内容,我找到了两个与马氏距离相关的MATLAB代码示例。以下是这两个示例:
1. 马氏距离的高亮检测统计方法:
```matlab
% 输入数据
data = [1 2 3; 4 5 6; 7 8 9];
% 计算协方差矩阵
covariance = cov(data);
% 计算协方差矩阵的逆矩阵
inverse_covariance = inv(covariance);
% 计算均值向量
mean_vector = mean(data);
% 计算马氏距离
mahalanobis_distance = mahal(data, mean_vector, inverse_covariance);
```
2. 马氏距离的计算公式代码表示:
```matlab
% 输入数据
data = [1 2 3; 4 5 6; 7 8 9];
% 计算均值向量
mean_vector = mean(data);
% 计算协方差矩阵
covariance = cov(data);
% 计算马氏距离
mahalanobis_distance = sqrt((data - mean_vector) * inv(covariance) * (data - mean_vector)');
```
相关问题
马氏距离的MATLAB代码
function d = mahalDist(X)
% MAHALDIST computes the Mahalanobis distance between each row of X and the mean of X
%
% Inputs:
% X - an n-by-p matrix of n observations of p variables
%
% Output:
% d - an n-by-1 vector of Mahalanobis distances
%
% Example:
% X = [1 2 3; 4 5 6; 7 8 9; 10 11 12];
% d = mahalDist(X);
% Compute the mean of X
mu = mean(X);
% Compute the covariance matrix of X
C = cov(X);
% Compute the inverse of C
Cinv = inv(C);
% Compute the Mahalanobis distance between each row of X and the mean of X
n = size(X,1);
d = zeros(n,1);
for i = 1:n
d(i) = sqrt((X(i,:) - mu)*Cinv*(X(i,:) - mu)');
end
end
马氏距离matlab代码
马氏距离是用于测量两个连续变量之间的距离,可以用以下Matlab代码实现:
```matlab
function d = mahal(x, mu, SIG)
% x是一个n维向量,mu是均值向量,SIG是协方差矩阵
% 返回x到mu的马氏距离
d = sqrt((x-mu)*inv(SIG)*(x-mu)');
end
```
其中,`x`是一个n维向量,`mu`是均值向量,`SIG`是协方差矩阵。函数返回`x`到`mu`的马氏距离。