代码如下;
let XGX= {correlationCoefficient(pA, pB) {let covXY = -pA * pBlet varX = pA * (1-pA) let varY = (1-pB)* pBlet res = covXY / (Math.sqrt(varX*varY, 2))return res},correlation(x,y){x=[0.3,50.2,99.5,199.3,299,398];y=[0.1,50,99.9,200,300,400];// 计算均值const avgX=x.reduce((a,b)=>a+b,0)/x.length;const avgY=y.reduce((a,b)=>a+b,0)/y.length;//计算差值const diffX=x.map((value,index)=>value-avgX);const diffY=y.map((value,index)=>value-avgY);//计算乘积const product =diffX.map((value,index)=>value*diffY[index]);//计算相关系数const sumProduct=product.reduce((a,b)=>a+b,0);const correlation=sumProduct/(x.length*y.length);return correlation},/*** 计算皮尔逊相关系数* @list1:数字列表1* @list2:数字列表2* @return number* */pearson(list1,list2){let newList = [];let len = list1.length;for(let i=0;i<len;i++){newList.push(list1[i]*list2[i]);}let mean1 = this.mean(list1),mean2=this.mean(list2);let cov = this.mean(newList)-mean1*mean2;return cov/(this.std(list1,mean1)*this.std(list2,mean2))},/*** 计算平均值* @list:数字列表* @return number* */mean(list){let sum = 0;list.forEach((item)=>{sum+=item})return sum/list.length;},/*** 计算标准差* @list:数字列表* @mean:列表list的平均值* @return number* */std(list,mean){let sum =0;list.forEach((item)=>{sum+=Math.pow(item-mean,2)})return Math.sqrt(sum/list.length)}
};
export default XGX调用：
效果：
