Example usage for org.apache.commons.math3.stat.regression SimpleRegression getSlopeStdErr

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.regression SimpleRegression getSlopeStdErr.

Prototype

public double getSlopeStdErr() 

Source Link

Document

Returns the <a href="http://www.xycoon.com/standerrorb(1).htm">standard error of the slope estimate</a>, usually denoted s(b1).

Usage

From source file:edu.ucsc.barrel.cdf_gen.ExtractTiming.java

public void fillModels() {
    int last_rec = 0, frame_i = 0, size_1Hz;
    long last_frame;
    SimpleRegression fit = null, new_fit = null;

    size_1Hz = data.getSize("1Hz");
    //create a model for each batch of time records
    for (int first_rec = 0; first_rec < time_rec_cnt; first_rec = last_rec) {
        //incriment the last_rec by the max, or however many recs are left
        last_rec += Math.min(MAX_RECS, (time_rec_cnt - first_rec));

        //try to generate a model
        new_fit = genModel(first_rec, last_rec);

        //Need to add better criteria than this for accepting a new model
        if (new_fit != null) {
            fit = new_fit;

            models[model_cnt] = new LinModel();
            models[model_cnt].setSlope(fit.getSlope());
            models[model_cnt].setIntercept(fit.getIntercept());
            models[model_cnt].setFirst(time_recs[first_rec].getFrame());
            models[model_cnt].setLast(time_recs[last_rec - 1].getFrame());
            model_cnt++;//from   w ww. j a va  2s .c o m

            System.out.println(
                    "Frames " + time_recs[first_rec].getFrame() + " - " + time_recs[last_rec - 1].getFrame());
            System.out.println("\tm = " + fit.getSlope() + ", b = " + fit.getIntercept() + " slope error = "
                    + fit.getSlopeStdErr() + " n = " + fit.getN());
        } else {
            System.out.println("Failed to get model using " + (last_rec - first_rec) + " records.");
        }
    }

    if (fit == null) {
        //no timing model was ever created. 
        //Use slope=1000 and intercept=0 to use frame number epoch.
        //this will clearly not give a good result for time, but will
        //allow the data to be plotted as a time series.
        //This will be a place to add a quality flag
        models[model_cnt] = new LinModel();
        models[model_cnt].setSlope(1000);
        models[model_cnt].setIntercept(0);
        models[model_cnt].setFirst(0);
        models[model_cnt].setLast(data.frame_1Hz[size_1Hz]);
        model_cnt = 1;
    }
}

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From source file:nl.systemsgenetics.cellTypeSpecificAlleleSpecificExpression.CTSlinearRegression.java

public CTSlinearRegression(ArrayList<IndividualSnpData> all_individuals) {

    //basic information, get the zero instance.
    snpName = all_individuals.get(0).getSnpName();
    chromosome = all_individuals.get(0).getChromosome();
    position = all_individuals.get(0).getPosition();

    //isolate heterozygotes
    ArrayList<IndividualSnpData> het_individuals = UtilityMethods
            .isolateValidHeterozygotesFromIndividualSnpData(all_individuals);
    numberOfHets = het_individuals.size();

    hetSampleNames = new ArrayList<String>();
    asRef = new ArrayList<Integer>();
    asAlt = new ArrayList<Integer>();
    asNo = new ArrayList<Integer>();

    cellProp = new ArrayList<Double>();
    int total_overlap = 0;

    //Get the basic data without doing any tests.
    for (IndividualSnpData temp_het : het_individuals) {
        //Do nothing if there is no data in het_individuals

        hetSampleNames.add(temp_het.getSampleName());

        asRef.add(temp_het.getRefNum());
        asAlt.add(temp_het.getAltNum());
        asNo.add(temp_het.getNoNum());/* ww  w .  ja v  a2 s.  c om*/
        cellProp.add(temp_het.getCellTypeProp());

        //this is used to check if we will continue with calculations.
        //BASED on the minHets and MinReads
        total_overlap += temp_het.getRefNum() + temp_het.getAltNum();
    }

    //Check if we do a test.
    if ((total_overlap >= GlobalVariables.minReads) && (numberOfHets >= GlobalVariables.minHets)
            && (numberOfHets >= 3)) {

        ASScatterPlot plotThis = null;

        if (!GlobalVariables.plotDir.equals("")) {
            plotThis = new ASScatterPlot(400);
        }

        SimpleRegression thisRegression = new SimpleRegression();
        for (int i = 0; i < asRef.size(); i++) {
            Double asRatio;
            //do this check, otherwise the denominator will be zero.

            if (asRef.get(i) != 0) {
                asRatio = ((double) asRef.get(i)) / ((double) (asRef.get(i) + asAlt.get(i)));
            } else {
                asRatio = 0.0;
            }

            Double phenoRatio = cellProp.get(i);
            thisRegression.addData(phenoRatio, asRatio);
            if (!GlobalVariables.plotDir.equals("")) {
                plotThis.plot(asRatio, phenoRatio);
            }
        }

        if (!GlobalVariables.plotDir.equals("")) {
            plotThis.draw(GlobalVariables.plotDir + "/" + snpName + "_ASratio_Pheno_Plot.png");
        }

        slope = thisRegression.getSlope();
        intercept = thisRegression.getIntercept();
        Rsquared = thisRegression.getRSquare();
        stdErrorIntercept = thisRegression.getInterceptStdErr();
        stdErrorSlope = thisRegression.getSlopeStdErr();

        pValue = thisRegression.getSignificance();

        if (GlobalVariables.verbosity >= 10) {
            System.out.println("\n--- Starting cell type specific linear regression ---");
            System.out.println("\tSlope:                   " + Double.toString(slope));
            System.out.println("\tStdError of Slope:       " + Double.toString(stdErrorSlope) + "\n");
            System.out.println("\tIntercept:               " + Double.toString(intercept));
            System.out.println("\tStdError of Intercept:   " + Double.toString(stdErrorIntercept) + "\n");
            System.out.println("\tP value:                 " + Double.toString(pValue));
            System.out.println("--------------------------------------------------------------");

        }

        testPerformed = true;
    }

}

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From source file:uk.ac.diamond.scisoft.ncd.core.data.plots.GuinierPlotData.java

private Amount<Dimensionless> getRg(SimpleRegression regression) {
    Amount<Dimensionless> slope = Amount.valueOf(regression.getSlope(), regression.getSlopeStdErr(),
            Dimensionless.UNIT);//  w  ww .  j a v a  2s.  c o  m
    Amount<Dimensionless> Rg = slope.times(-3.0).sqrt().to(Dimensionless.UNIT);
    return Rg.copy();
}

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