java实现独立性检验

缺乏、安全感 2023-06-28 04:54 47阅读 0赞

### 文章目录 ###

*   *  场景
     *  maven依赖
     *  用法
     *  实现代码

## 场景 ##

用于两个分类变量间的比较。

## maven依赖 ##

<dependency>
    			<groupId>net.sf.jsci</groupId>
    			<artifactId>jsci</artifactId>
    			<version>1.2</version>
    		</dependency>
    		
    		<dependency>
    			<groupId>org.apache.commons</groupId>
    			<artifactId>commons-math3</artifactId>
    			<version>3.6.1</version>
    		</dependency>
    
    	</dependencies>

## 用法 ##

package com.math.demo;
    
    import java.util.HashMap;
    import java.util.Map;
    
    import com.math.statistics.IndependenceTest;
    
    public class IndependenceDemo {
    
    	public static void main(String[] args) {
    		Map<String, Double> map1=new HashMap<String, Double>();
    		map1.put("a", 51.0);
    		map1.put("b", 56.0);
    		map1.put("c", 25.0);
    		Map<String, Double> map2=new HashMap<String, Double>();
    		map2.put("a", 39.0);
    		map2.put("b", 21.0);
    		map2.put("c", 8.0);
    		IndependenceTest it=new IndependenceTest(map1,map2);
    		System.out.println(it.getPValue());
    
    	}
    
    }

## 实现代码 ##

package com.math.statistics;
    
    import java.util.HashMap;
    import java.util.Map;
    import java.util.Set;
    
    import JSci.maths.statistics.ChiSqrDistribution;
    
    public class IndependenceTest {
    
    	private Map<String, Double> map1;
    
    	private Map<String, Double> map2;
    
    	public IndependenceTest(Map<String, Double> map1, Map<String, Double> map2) {
    		super();
    		this.map1 = map1;
    		this.map2 = map2;
    	}
    
    	public double getSum() {
    		double sum1 = map1.values().stream().reduce(Double::sum).orElse((double) 0);
    		double sum2 = map2.values().stream().reduce(Double::sum).orElse((double) 0);
    		return sum1 + sum2;
    	}
    
    	public double getMap1Sum() {
    		return map1.values().stream().reduce(Double::sum).orElse((double) 0);
    	}
    
    	public double getMap2Sum() {
    		return map2.values().stream().reduce(Double::sum).orElse((double) 0);
    	}
    
    	/**
    	 * 2为map的数量
    	 * 
    	 * @return
    	 */
    	public double getDegreesOfFreedom() {
    		return (map1.keySet().size() - 1) * (2 - 1);
    	}
    
    	public Map<String, Double> getScale() {
    		Set<String> keySet = map1.keySet();
    		Map<String, Double> scale = new HashMap<String, Double>();
    		for (String key : keySet) {
    			scale.put(key, (map1.get(key) + map2.get(key)) / getSum());
    		}
    		return scale;
    	}
    
    	public double getPValue() {
    		double map1Sum = getMap1Sum();
    		double map2Sum = getMap2Sum();
    		double x = 0;
    		Map<String, Double> scale = getScale();
    		Set<String> keySet = map1.keySet();
    		for (String key : keySet) {
    			double sampleValue1 = map1.get(key);
    			double expectValue1 = map1Sum * scale.get(key);
    			double map1KeyFre = ((sampleValue1 - expectValue1) * (sampleValue1 - expectValue1)) / expectValue1;
    
    			double sampleValue2 = map2.get(key);
    			double expectValue2 = map2Sum * scale.get(key);
    			double map2KeyFre = ((sampleValue2 - expectValue2) * (sampleValue2 - expectValue2)) / expectValue2;
    
    			x = x + map1KeyFre + map2KeyFre;
    
    		}
    		ChiSqrDistribution cd = new ChiSqrDistribution(getDegreesOfFreedom());
    		return 1 - cd.cumulative(x);
    	}
    
    }