java – R.loess和org.apache.commons.math之间的区别LoessInterpolator

我正在尝试使用apache.commons.math库来计算将R脚本转换为 java脚本.可以使用 org.apache.commons.math.analysis.interpolation.LoessInterpolator代替 R loess吗？我得不到同样的结果.

编辑.

这里是一个java程序,它创建一个随机数组(x,y),并用LoessInterpolator或者调用R来计算黄土.最后打印结果.

import java.io.*;
import java.util.Random;

import org.apache.commons.math.analysis.interpolation.LoessInterpolator;


public class TestLoess
    {
    private String RScript="/usr/local/bin/Rscript";
    private static class ConsummeInputStream
        extends Thread
        {
        private InputStream in;
        ConsummeInputStream(InputStream in)
            {
            this.in=in;
            }
        @Override
        public void run()
            {
            try
                {
                int c;
                while((c=this.in.read())!=-1) 
                    System.err.print((char)c);
                }
            catch(IOException err)
                {
                err.printStackTrace();
                }
            }
        }
    TestLoess()
        {

        }
    private void run() throws Exception
        {
        int num=100;
        Random rand=new Random(0L);
        double x[]=new double[num];
        double y[]=new double[x.length];
        for(int i=0;i< x.length;++i)
            {
            x[i]=rand.nextDouble()+(i>0?x[i-1]:0);
            y[i]=Math.sin(i)*100;
            }
        LoessInterpolator loessInterpolator=new LoessInterpolator(
            0.75,//bandwidth,2//robustnessIters

            );
        double y2[]=loessInterpolator.smooth(x,y);

        Process proc=Runtime.getRuntime().exec(
            new String[]{RScript,"-"}
            );
        ConsummeInputStream errIn=new ConsummeInputStream(proc.getErrorStream());
        BufferedReader stdin=new BufferedReader(new InputStreamReader(proc.getInputStream()));
        PrintStream out=new PrintStream(proc.getOutputStream());
        errIn.start();
        out.print("T<-as.data.frame(matrix(c(");
        for(int i=0;i< x.length;++i)
            {
            if(i>0) out.print(',');
            out.print(x[i]+","+y[i]);
            }
        out.println("),ncol=2,byrow=TRUE))");
        out.println("colnames(T)<-c('x','y')");
        out.println("T2<-loess(y ~ x,T)");
        out.println("write.table(residuals(T2),'',col.names= F,row.names=F,sep='t')");
        out.flush();
        out.close();
        double y3[]=new double[x.length];
        for(int i=0;i< y3.length;++i)
            {
            y3[i]=Double.parseDouble(stdin.readLine());
            }
        System.out.println("XtYtY.javatY.R");
        for(int i=0;i< y3.length;++i)
            {
            System.out.println(""+x[i]+"t"+y[i]+"t"+y2[i]+"t"+y3[i]);
            }
        }

    public static void main(String[] args)
        throws Exception
        {
        new TestLoess().run();
        }
    }

编译& EXEC：

javac -cp commons-math-2.2.jar TestLoess.java && java -cp commons-math-2.2.jar:. TestLoess

输出：

X   Y   Y.java  Y.R
0.730967787376657   0.0 6.624884763714674   -12.5936186703287
0.9715042030481429  84.14709848078965   6.5263049649584 71.9725380029913
1.6089216283982513  90.92974268256818   6.269100654071115   79.839773167581
2.159358633515885   14.112000805986721  6.051308261720918   3.9270340708818
2.756903911313087   -75.68024953079282  5.818424835586378   -84.9176311089431
3.090122310789737   -95.89242746631385  5.689740879461759   -104.617807889069
3.4753114955304554  -27.941549819892586 5.541837854229562   -36.0902352062634
4.460153035730264   65.6986598718789    5.168028655980764   58.9472823439219
5.339335553602744   98.93582466233818   4.840314399516663   93.3329030534449
6.280584733084859   41.21184852417566   4.49531113985498    36.7282165788057
6.555538699120343   -54.40211108893698  4.395343460231256   -58.5812856445538
6.68443584999412    -99.99902065507035  4.348559404444451   -104.039069260889
6.831037507640638   -53.657291800043495 4.295400167908642   -57.5419313320511
6.854275630124528   42.016703682664094  4.286978656933373   38.1564179414478
7.401015387322993   99.06073556948704   4.089252482141094   95.7504087842369
8.365502247999844   65.02878401571168   3.7422883733498726  62.5865641279576
8.469992934250815   -28.790331666506532 3.704793544880599   -31.145867173504
9.095139297716374   -96.13974918795569  3.4805388562453574  -98.0047896609079
9.505935493207435   -75.09872467716761  3.3330472034239405  -76.6664588290508

y的输出值在R和Java之间显然不一样; TheY.R列看起来不错(它接近原始的Y列).为了得到Y.javaY.R,我该怎么改？

解决方法

> Java LoessInterpolator只进行线性局部多项式回归,但R支持线性(度= 1),二次(度= 2)和奇数度= 0选项.所以你需要在R中指定degree = 1来与Java相同.> LoessInterpolator默认迭代次数DEFAULT_ROBUSTNESS_ITERS = 2,但是R默认迭代= 4.所以你需要在R中设置control = loess.control(iterations = X)(X是迭代次数).> LoessInterpolator默认为DEFAULT_BANDWIDTH = 0.3,但R默认为span = 0.75.

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