Examples of com.mockturtlesolutions.snifflib.invprobs.FixedSmoothMethod

    Lpreg lpreg = new Lpreg(pHi,LOF);
    System.out.println("Finished instantiating Lpreg");
    
    System.out.println("Setting smoothing parameter...");
    NNBandwidth BW = (NNBandwidth)lpreg.getBandwidthMethod();
    FixedSmoothMethod SM = (FixedSmoothMethod)BW.getSmoothMethod();
    DblMatrix sp = this.getParam("smoothing_param");
    
    if (DblMatrix.test(sp.lt(0.01))) //Can't let window get so small that the number of data points is less than the model df+1+number of derivatives you want to estimate.
    {
      return(DblMatrix.INF);
    }
    
    SM.setSmoothParameter(sp.getDoubleAt(0)); //The proportion of N that gives K in the NN method.
    System.out.println("Finished setting smoothing parameter...");
    
    
    System.out.println("Lpreg prediction...");
    //DblMatrix LOFhat = lpreg.predict(pHi); //These should be iid Normal


              DblMatrix[] XDATA = new DblMatrix[]{SmoothingpH};
               DblMatrix YDATA = SmoothingCbResidual;
               SmoothingSmoother.setData(XDATA,YDATA);
              NNBandwidth BW = (NNBandwidth)SmoothingSmoother.getBandwidthMethod();
              FixedSmoothMethod SM  = (FixedSmoothMethod)BW.getSmoothMethod();
              DblMatrix SP = smoothingParameter.divideBy(smoothingParameter.plus(1.0));


              SM.setSmoothParameter(SP); 
              BW.setSmoothMethod(SM);
            }
            else if (((Integer)this.adjustForMap.get("adjustForSmoothingMethod")).intValue() == DefaultComplexBufferPredictorGenerator.POLYNOMIAL_SMOOTHING)
            {
              SmoothingpH = (DblMatrix)this.smoothingpHMap.get(mapkey1);

Examples of com.mockturtlesolutions.snifflib.invprobs.FixedSmoothMethod

Related Classes of com.mockturtlesolutions.snifflib.invprobs.FixedSmoothMethod