Package com.nr.sf

Examples of com.nr.sf.Normaldist

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    invsq2pi=1.0/sqrt(2.0*pi);

    // Test special cases
    sbeps=1.e-15;
    m=0; s=1; u=0;
    Normaldist norm1 = new Normaldist(m,s);
    localflag = localflag || abs(norm1.p(u) - invsq2pi) > sbeps;
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Special case #1 failed");
     
    }

    m=1; s=1; u=m;
    Normaldist norm2 = new Normaldist(m,s);
    localflag = localflag || abs(norm2.p(u) - invsq2pi) > sbeps;
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Special case #2 failed");
     
    }

    m=1; s=1; u=0;
    Normaldist norm3 = new Normaldist(m,s);
    localflag = localflag || abs(norm3.p(u) - invsq2pi*exp(-0.5)) > sbeps;
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Special case #3 failed");
     
    }

    m=1; s=2; u=1;
    Normaldist norm4 = new Normaldist(m,s);
    localflag = localflag || abs(norm4.p(u) - invsq2pi/2.0) > sbeps;
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Special case #4 failed");
     
    }

    m=1; s=2; u=0;
    Normaldist norm5 = new Normaldist(m,s);
    localflag = localflag || abs(norm5.p(u) - invsq2pi/2.0*exp(-1.0/8.0)) > sbeps;
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Special case #5 failed");
     
    }

    // integral of distribution is one
    sbeps=1.e-10;
    m=1.0;s=2.0;
    func_Normaldist dist = new func_Normaldist(m,s);
    localflag = abs(1.0-qsimp(dist,-20.0,20.0)) > sbeps;
    //  System.out.printf(setprecision(15) << 1.0-qsimp(dist,-20.0,20.0));
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Distribution is not normalized to 1.0");
     
    }

    // cdf agrees with incomplete integral
    sbeps=1.e-10;
    m=0.5;s=1.5;
    func_Normaldist dist2 =new func_Normaldist(m,s);
    Normaldist normcdf = new Normaldist(m,s);
    for (i=0;i<N;i++) {
      c[i]=qsimp(dist2,-20.0,x[i]);
      d[i]=normcdf.cdf(x[i]);
//      System.out.printf(c[i]-d[i]);
      localflag = localflag || abs(c[i]-d[i]) > sbeps;
    }
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: cdf does not agree with result of quadrature");
     
    }
   
    // inverse cdf agrees with cdf
    m=0.5;s=1.5;
    Normaldist normc = new Normaldist(m,s);
    Ran myran = new Ran(17);
    sbeps=5.0e-14;
    for (i=0;i<1000;i++) {
      u=m-3.0*s+6.0*s*myran.doub();
      a=normc.cdf(u);
      b=normc.invcdf(a);
//      System.out.printf(setprecision(15) << u << " %f\n", b << " %f\n", abs(u-b));
      localflag = localflag || abs(u-b) > sbeps;
    }
    globalflag = globalflag || localflag;
    if (localflag) {
      fail("*** Normaldist: Inverse cdf does not accurately invert the cdf");
     
    }
     
    // Fingerprint test
    m=0.5;s=1.5;
    Normaldist normf = new Normaldist(m,s);
    for (i=0;i<N;i++) {
      p[i]=normf.p(x[i]);
//      System.out.printf(setprecision(17) << p[i] << " %f\n", pexp[i]);
    }
//    System.out.println("Normaldist: Maximum discrepancy = %f\n", maxel(vecsub(p,pexp)));
    localflag = localflag || maxel(vecsub(p,pexp)) > sbeps;
    globalflag = globalflag || localflag;
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  class func_Normaldist implements UniVarRealValueFun{
    double m,s;
    Normaldist normi;
    func_Normaldist(double mm, double ss) {
      m=mm;s=ss;
      normi = new Normaldist(m,s);
    };
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      fail("*** Normaldev_BM: dev() does not match fingerprint");
     
    }

    // Check statistics
    Normaldist expect = new Normaldist(mu,sig);
    xl=mu-range/2.0;
    xu=mu+range/2.0;
    binsize=range/M;
    for (i=0;i<M;i++) {
      x[i]=xl+binsize*i;
      ebins[i]=N*binsize*expect.p(x[i]+0.5*binsize);
      bins[i]=0;
    }
    for (i=0;i<N;i++) {
      nbin=(int)(floor((0.5*range+myran.dev())/binsize));
      if ((nbin >= 0) && (nbin < M)) bins[nbin] += 1;
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      fail("*** Normaldev: dev() does not match fingerprint");
     
    }

    // Check statistics
    Normaldist expect = new Normaldist(mu,sig);
    xl=mu-range/2.0;
    xu=mu+range/2.0;
    binsize=range/M;
    for (i=0;i<M;i++) {
      x[i]=xl+binsize*i;
      ebins[i]=N*binsize*expect.p(x[i]+0.5*binsize);
      bins[i]=0;
    }
    for (i=0;i<N;i++) {
      nbin=(int)(floor((0.5*range+myran.dev())/binsize));
      if ((nbin >= 0) && (nbin < M)) bins[nbin] += 1;
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Related Classes of com.nr.sf.Normaldist

  • com.nr.test.test_chapter6.Test_Normaldist
  • com.nr.test.test_chapter6.Test_Normaldist$func_Normaldist
  • com.nr.test.test_chapter7.Test_Normaldev
  • com.nr.test.test_chapter7.Test_Normaldev_BM
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