查找协方差的程序

给定两组随机变量，找到协方差。协方差是两个随机变量一起变化的量度。它与方差相似，但是方差告诉您单个变量如何变化，协方差告诉您两个变量如何一起变化。可以使用以下公式计算协方差
${\displaystyle \operatorname {cov} (X,Y)={\frac {1}{n}}\sum _{i=1}^{n}(x_{i}-x')(y_{i}-y').}$
其中x’和y’是两个给定集合的均值。

例子：

Input : arr1[] = {65.21, 64.75, 65.26, 65.76, 65.96}
        arr2[] = {67.25, 66.39, 66.12, 65.70, 66.64}
Output : -0.0580511

Input : arr1[] = {5, 20, 40, 80, 100}
        arr2[] = {10, 24, 33, 54, 10}
Output : 187.75

C++

// C++ Program to find
// covariance of two set.
#include
using namespace std;
 
// Function to find mean.
float mean(float arr[], int n)
{
    float sum = 0;
    for(int i = 0; i < n; i++)
        sum = sum + arr[i];
    return sum / n;
}
 
// Function to find covariance.
float covariance(float arr1[], float arr2[], int n)
{
    float sum = 0;
    for(int i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean(arr1, n)) *
                    (arr2[i] - mean(arr2, n));
    return sum / (n - 1);
}
 
// Driver function.
int main()
{
    float arr1[] = {65.21, 64.75, 65.26, 65.76, 65.96};
    int n = sizeof(arr1) / sizeof(arr1[0]);
     
    float arr2[] = {67.25, 66.39, 66.12, 65.70, 66.64};
    int m = sizeof(arr2) / sizeof(arr2[0]);
     
    if (m == n)
        cout << covariance(arr1, arr2, m);
    return 0;
}

Java

// Java Program to find
// covariance of two set.
import java.io.*;
 
class GFG {
 
// Function to find mean.
static float mean(float arr[], int n)
{
    float sum = 0;
     
    for(int i = 0; i < n; i++)
        sum = sum + arr[i];
     
    return sum / n;
}
 
// Function to find covariance.
static float covariance(float arr1[],
                    float arr2[], int n)
{
    float sum = 0;
     
    for(int i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean(arr1, n)) *
                        (arr2[i] - mean(arr2, n));
    return sum / (n - 1);
}
 
// Driver code
    public static void main (String[] args) {
     
    float arr1[] = {65.21f, 64.75f,
               65.26f, 65.76f, 65.96f};
    int n = arr1.length;
     
    float arr2[] = {67.25f, 66.39f,
                66.12f, 65.70f, 66.64f};
     
    int m = arr2.length;
     
    if (m == n)
     
    System.out.println(covariance(arr1, arr2, m));
     
    }
}
 
// This code is contributed by Gitanjali.

Python3

# Python3 Program to find
# covariance of two set.
import math
 
# Function to find mean.
def mean(arr, n):
     
    sum = 0
    for i in range(0, n):
        sum = sum + arr[i]
     
    return sum / n
 
# Function to find covariance.
def covariance(arr1, arr2, n):
 
    sum = 0
    for i in range(0, n):
        sum = (sum + (arr1[i] - mean(arr1, n)) *
                      (arr2[i] - mean(arr2, n)))
     
    return sum / (n - 1)
 
# Driver method
arr1 = [65.21, 64.75, 65.26, 65.76, 65.96]
n = len(arr1)
 
arr2 = [67.25, 66.39, 66.12, 65.70, 66.64]
m = len(arr2)
 
if (m == n):
    print (covariance(arr1, arr2, m))
 
# This code is contributed by Gitanjali.

C#

// C# Program to find
// covariance of two set.
using System;
 
class GFG {
 
    // Function to find mean.
    static float mean(float []arr, int n)
    {
        float sum = 0;
         
        for(int i = 0; i < n; i++)
            sum = sum + arr[i];
         
        return sum / n;
    }
     
    // Function to find covariance.
    static float covariance(float []arr1,
                        float []arr2, int n)
    {
        float sum = 0;
         
        for(int i = 0; i < n; i++)
            sum = sum + (arr1[i] - mean(arr1, n)) *
                            (arr2[i] - mean(arr2, n));
        return sum / (n - 1);
    }
     
    // Driver code
    public static void Main () {
     
        float []arr1 = {65.21f, 64.75f,
                65.26f, 65.76f, 65.96f};
        int n = arr1.Length;
         
        float []arr2 = {67.25f, 66.39f,
                    66.12f, 65.70f, 66.64f};
         
        int m = arr2.Length;
         
        if (m == n)
         
        Console.WriteLine(covariance(arr1, arr2, m));
     
    }
}
 
// This code is contributed by vt_m.

Javascript

 
// Javascript program to find
// covariance of two set.
 
// Function to find mean.
function mean(arr, n)
{
    let sum = 0;
    for(let i = 0; i < n; i++)
        sum = sum + arr[i];
         
    return sum / n;
}
 
// Function to find covariance.
function covariance(arr1, arr2, n)
{
    let sum = 0;
    for(let i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean(arr1, n)) *
                    (arr2[i] - mean(arr2, n));
                     
    return sum / (n - 1);
}
 
// Driver code
let arr1 = [ 65.21, 64.75, 65.26, 65.76, 65.96 ];
let n = arr1.length;
 
let arr2 = [ 67.25, 66.39, 66.12, 65.70, 66.64 ];
let m = arr2.length;
 
if (m == n)
    document.write(covariance(arr1, arr2, m));
     
// This code is contributed by souravmahato348
 

输出：

-0.0580511