Package fork.lib.math.applied.stat

Examples of fork.lib.math.applied.stat.Distribution.mean()

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            dis.add(Integer.parseInt(ss));
        }
    }
    out= out.substring(0, out.length()-1);
    out+=")";
    out+="\nmu:"+dis.mean()+"   zero:"+ (double)dis.subsetLowerOrEqualTo(0).size()/dis.size()
            +"  me:"+dis.median()+"   s:"+dis.standartDeviation();
    return out;
}
   
   
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    Distribution dis0 = new BedGraphBuffer(outRat).getDistributionNonZero();
    Distribution dis= dis0.subsetHigherThan(1);
    dis= dis.subsetLowerOrEqualTo(dis.quantileBoundaries(10).get(5));
   
   
    double mean= dis.mean();
    double sd= dis.standartDeviation();
    double rat= mean+ 1.2 *sd;
   
    System.out.println("m: "+ mean+"   sd: "+sd+"  rat: "+rat);
   
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    Distribution d= lb.getDistributionNonZero();
    ArrayList<Double> qs= d.quantileBoundaries(100);
    double m=0 ,sd=0;
    for( int i=0; i<50; i++ ){
        Distribution df= d.subset(qs.get(i), qs.get(qs.size()-1-i), true, true);
        m= df.mean();
        sd= df.standartDeviation();
        double z= sd/m;
        //System.out.println(i+"   mean: "+m+"   med: "+med+"   sd: "+ sd+"  z:"+z);
        if(z<0.2){
            break;
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    Distribution d= lb.getDistributionNonZero();
    ArrayList<Double> qs= d.quantileBoundaries(100);
    double m=0 ,sd=0;
    for( int i=0; i<50; i++ ){
        Distribution df= d.subset(qs.get(i), qs.get(qs.size()-1-i), true, true);
        m= df.mean();
        double med= df.median();
        sd= df.standartDeviation();
        double z= sd/m;
        //System.out.println(i+"   mean: "+m+"   med: "+med+"   sd: "+ sd+"  z:"+z);
        if(z<0.2){
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