APACHE common中的统计学工具
package com.njs.math;
import org.apache.commons.math.stat.descriptive.moment.GeometricMean;
import org.apache.commons.math.stat.descriptive.moment.Kurtosis;
import org.apache.commons.math.stat.descriptive.moment.Mean;
import org.apache.commons.math.stat.descriptive.moment.Skewness;
import org.apache.commons.math.stat.descriptive.moment.StandardDeviation;
import org.apache.commons.math.stat.descriptive.moment.Variance;
import org.apache.commons.math.stat.descriptive.rank.Max;
import org.apache.commons.math.stat.descriptive.rank.Min;
import org.apache.commons.math.stat.descriptive.rank.Percentile;
import org.apache.commons.math.stat.descriptive.summary.Product;
import org.apache.commons.math.stat.descriptive.summary.Sum;
import org.apache.commons.math.stat.descriptive.summary.SumOfSquares;
public class MathDemo {
/**
* @param args
*/
public static void main(String[] args) {
double[] values = new double[] { 0.33, 1.33, 0.27333, 0.3, 0.501,
0.444, 0.44, 0.34496, 0.33, 0.3, 0.292, 0.667 };
Min min = new Min(); // 最小
Max max = new Max(); // 最大
Mean mean = new Mean(); // 算术平均值
Product product = new Product();// 所有数相乘
Sum sum = new Sum(); // 算术和
Variance variance = new Variance(); // 方差
System.out.println("min: " + min.evaluate(values));
System.out.println("max: " + max.evaluate(values));
System.out.println("mean: " + mean.evaluate(values));
System.out.println("product: " + product.evaluate(values));
System.out.println("sum: " + sum.evaluate(values));
System.out.println("variance: " + variance.evaluate(values));
/**
* percentile(array,p)算法一般是：将数组array从小到大排序，计算(n-1)*p的整数部分为i，小数部分为j，其中n为数组大小，则percentile的值是：(1-j)*array第i+1个数+j*array第i+2个数。
* 例如：{1，3，4，5，6，7，8，9，19，29，39，49，59，69，79，80}计算30%的分位数：
* (16-1)*30%=4.5, i= 4, j =0.5
* percentile(a,30%)=(1-0.5)*6+0.5*7=6.5
* */
Percentile percentile = new Percentile(); // 百分位数
GeometricMean geoMean = new GeometricMean(); // 几何平均数,n个正数的连乘积的n次算术根叫做这n个数的几何平均数
Skewness skewness = new Skewness(); // Skewness 偏度;
Kurtosis kurtosis = new Kurtosis(); // Kurtosis 峰度
SumOfSquares sumOfSquares = new SumOfSquares(); // 平方和
StandardDeviation StandardDeviation = new StandardDeviation();// 标准方差
System.out.println("80 percentile value: " + percentile.evaluate(values, 80.0));
System.out.println("geometric mean: " + geoMean.evaluate(values));
System.out.println("skewness: " + skewness.evaluate(values));
System.out.println("kurtosis: " + kurtosis.evaluate(values));
System.out.println("sumOfSquares: " + sumOfSquares.evaluate(values));
System.out.println("StandardDeviation: " + StandardDeviation.evaluate(values));
}
}