I am searching a lot but could not find exactly what i need till now.
I have two integer arrayas int[] x
and int[] y
. I want to find simple linear correlation between these two integer arrays and it should return the result as double
. In java do you know any library function providing this or any code snippet?
Arrays. equals(Object[] a, Object[] a2) method returns true if the two specified arrays of objects are equal to one another. The two arrays are considered equal if both arrays contain the same number of elements, and all corresponding pairs of elements in the two arrays are equal.
The Pearson's correlation coefficient is calculated as the covariance of the two variables divided by the product of the standard deviation of each data sample. It is the normalization of the covariance between the two variables to give an interpretable score.
There is nothing in core Java. There are libraries out there you can use. Apache Commons has a statistical project, check PearsonCorrelation class.
Sample code:
public static void main(String[] args) {
double[] x = {1, 2, 4, 8};
double[] y = {2, 4, 8, 16};
double corr = new PearsonsCorrelation().correlation(y, x);
System.out.println(corr);
}
prints out 1.0
Correlation is quite easy to compute manually:
http://en.wikipedia.org/wiki/Correlation_and_dependence
public static double Correlation(int[] xs, int[] ys) {
//TODO: check here that arrays are not null, of the same length etc
double sx = 0.0;
double sy = 0.0;
double sxx = 0.0;
double syy = 0.0;
double sxy = 0.0;
int n = xs.length;
for(int i = 0; i < n; ++i) {
double x = xs[i];
double y = ys[i];
sx += x;
sy += y;
sxx += x * x;
syy += y * y;
sxy += x * y;
}
// covariation
double cov = sxy / n - sx * sy / n / n;
// standard error of x
double sigmax = Math.sqrt(sxx / n - sx * sx / n / n);
// standard error of y
double sigmay = Math.sqrt(syy / n - sy * sy / n / n);
// correlation is just a normalized covariation
return cov / sigmax / sigmay;
}
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With