public double[][] getXYMinMax() {
int[] indicesX = new int[x.length];
int[] indicesY = new int[y.length];
HeapSort.sort(x, indicesX);
HeapSort.sort(y, indicesY);
double[][] returnArray = new double[2][2];
returnArray[0][0] = x[indicesX[0]];
returnArray[0][1] = x[indicesX[indicesX.length - 1]];
returnArray[1][0] = y[indicesY[0]];
returnArray[1][1] = y[indicesY[indicesY.length - 1]];
return returnArray;
}
/**
* compute median
*
* @param x list of numbers
* @return median
*/
public static double median(double[] x) {
if (x == null || x.length == 0) {
throw new IllegalArgumentException();
}
int[] indices = new int[x.length];
HeapSort.sort(x, indices);
return median(x, indices);
}
/**
* compute the cumulative probability Pr(x <= z) for a given z and a distribution of x
*
* @param z threshold value
* @param x discrete distribution (an unordered list of numbers)
* @return cumulative probability
*/
public static double cdf(double z, double[] x) {
int[] indices = new int[x.length];
HeapSort.sort(x, indices);
return cdf(z, x, indices);
}
/**
* compute the q-th quantile for a distribution of x (= inverse cdf)
*
* @param q quantile (0 <= q <= 1)
* @param x discrete distribution (an unordered list of numbers)
* @param count use only first count entries in x
* @return q-th quantile
*/
public static double quantile(double q, double[] x, int count) {
int[] indices = new int[count];
HeapSort.sort(x, indices);
return quantile(q, x, indices);
}
/**
* compute the q-th quantile for a distribution of x (= inverse cdf)
*
* @param q quantile (0 <= q <= 1)
* @param x discrete distribution (an unordered list of numbers)
* @return q-th quantile
*/
public static double quantile(double q, double[] x) {
int[] indices = new int[x.length];
HeapSort.sort(x, indices);
return quantile(q, x, indices);
}
