Java Utililty Methods mean

List of utility methods to do mean

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Description

The list of methods to do mean are organized into topic(s).

Method

double[]meanAndVariance(double[] a, boolean useUnbiasedEstimate)
Computes the mean and variance of the input array and returns the result as a two-element double array: {mean, variance}}, using a numerically stable algorithm described by Welford. 
return meanAndVariance(a, useUnbiasedEstimate, 0, a.length);
doublemeanArithmetic(LinkedList a)
mean Arithmetic 
int n = a.size();
double sum = 0.0;
for (int i = 0; i < a.size(); i++) {
    sum = sum + a.get(i);
return sum / n;
doublemeanArray(double[] arr)
Method to calculate mean of an array 
double out = 0.0;
for (int i = 0; i < arr.length; i++)
    out += arr[i];
return out / (1.0 * arr.length);
doublemeandiff(double[] v1, double[] v2)
Returns the difference in the means of the two lists. 
double s1 = 0, c1 = 0;
for (int i = 0; i < v1.length; i++) {
    s1 += v1[i];
    c1++;
double m1 = s1 / c1;
double s2 = 0, c2 = 0;
for (int i = 0; i < v2.length; i++) {
...
doublemeanEnt(double[] nums)
Return the mean entropy of the logs of the numbers given. 
return logProb(nums) / nums.length;
doublemeanFast(final double[] values)
mean Fast 
return sumFast(values) / values.length;
float[]meanFilter(float[] weights, int context)
Performs mean filtering of the array. 
float meanFiltered[] = new float[weights.length];
float mean = 0;
for (int i = 0; i < weights.length; i++) {
    if (i > context / 2) {
        mean -= weights[i - (context / 2)];
    if (i < (weights.length - 1) - (context / 2)) {
        mean += weights[i + (context / 2)];
...
doublemeanGreenwichSideralTime(double t)
mean Greenwich Sideral Time 
double theta = 100.46061837 + 36000.770053608 * t + 0.000387933 * (t * t) - (t * t * t) / 38710000;
while (theta > 360.0) {
    theta -= 360.0;
while (theta < 0.0) {
    theta += 360.0;
return theta;
...
float[][]meanImage(float[][]... images)
Calculates the mean of multiple images through each pixel 
int count = images.length;
float[][] mean_float_mat = new float[images[0].length][images[0][0].length];
for (int i = 0; i < images[0].length; i++) {
    for (int j = 0; j < images[0][0].length; j++) {
        float sum = 0;
        for (float[][] float_mat : images) {
            sum += float_mat[i][j];
        mean_float_mat[i][j] = sum / count;
return mean_float_mat;
intmeanLow(final int a, final int b)
mean Low 
return (a & b) + ((a ^ b) >> 1);