Programa para hallar covarianza

Posted on by Rudeus Greyrat

Dado un conjunto de dos variables aleatorias, encuentre la covarianza. La covarianza es una medida de cuánto varían juntas dos variables aleatorias. Es similar a la varianza, pero donde la varianza te dice cómo varía una sola variable, la covarianza te dice cómo varían dos variables juntas. La covarianza se puede calcular usando la fórmula 
{\displaystyle \operatorname {cov} (X,Y)={\frac {1}{n}}\sum _{i=1}^{n}(x_{i}-x')(y_{i}-y').}
Donde x’ y y’ son las medias de dos conjuntos dados.

Ejemplos: 

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 <bits/stdc++.h>
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;
    float mean_arr1 = mean(arr1, n);
    float mean_arr2 = mean(arr2, n);
    for (int i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean_arr1) * (arr2[i] - mean_arr2);
    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;
}
 
// This code is contributed by Aditya Kumar (adityakumar129)

C

// C Program to find covariance of two set.
#include <stdio.h>
 
// 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;
    float mean_arr1 = mean(arr1, n);
    float mean_arr2 = mean(arr2, n);
    for (int i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean_arr1) * (arr2[i] - mean_arr2);
    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)
        printf("%f", covariance(arr1, arr2, m));
    return 0;
}
 
// This code is contributed by Aditya Kumar (adityakumar129)

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;
        float mean_arr1 = mean(arr1, n);
        float mean_arr2 = mean(arr2, n);
 
        for (int i = 0; i < n; i++)
            sum = sum + (arr1[i] - mean_arr1) * (arr2[i] - mean_arr2);
        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 Aditya Kumar (adityakumar129)

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
    mean_arr1 = mean(arr1, n)
    mean_arr2 = mean(arr2, n)
    for i in range(0, n):
        sum = (sum + (arr1[i] - mean_arr1) * (arr2[i] - mean_arr2))
 
    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 Aditya Kumar (adityakumar129)

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;
          float mean_arr1 = mean(arr1,n);
          float mean_arr2 = mean(arr2,n);   
        for(int i = 0; i < n; i++)
            sum = sum + (arr1[i] - mean_arr1) *
                            (arr2[i] - mean_arr2);
        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.

PHP

<?php
// PHP Program to find
// covariance of two set.
 
// Function to find mean.
function mean( $arr, $n)
{
    $sum = 0;
    for( $i = 0; $i < $n; $i++)
        $sum = $sum + $arr[$i];
    return $sum / $n;
}
 
// Function to find covariance.
function covariance( $arr1, $arr2, $n)
{
    $sum = 0;
    $mean_arr1 = mean($arr1,$n);
      $mean_arr2 = mean($arr2,$n);
    for( $i = 0; $i < $n; $i++)
        $sum = $sum + ($arr1[$i] -
                 $mean_arr1) *
                      ($arr2[$i] -
                  $mean_arr2);
    return $sum / ($n - 1);
}
 
// Driver function.
$arr1 = array(65.21, 64.75, 65.26,
                        65.76, 65.96);
$n = count($arr1);
     
$arr2 = array(67.25, 66.39, 66.12,
                        65.70, 66.64);
$m =count($arr2);
     
if ($m == $n)
    echo covariance($arr1, $arr2, $m);
 
// This code is contributed by anuj_67.
?>

Javascript

<script>
 
// 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;
     let mean_arr1 = mean(arr1, n);
    let mean_arr2 = mean(arr2, n);
    for(let i = 0; i < n; i++)
        sum = sum + (arr1[i] - mean_arr1) *
                    (arr2[i] - mean_arr2);
                     
    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
 
</script>

Producción: 

-0.0580511

Complejidad temporal: O(N)
Espacio auxiliar: O(1) 
 

Publicación traducida automáticamente

Artículo escrito por Dharmendra_Kumar y traducido por Barcelona Geeks. The original can be accessed here. Licence: CCBY-SA

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