Examples of linear()

Examples of flanagan.analysis.Regression.linear()

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        // Obtain the intercept and gradient of the Gaussian probabilty plot
        ArrayMaths st4 = new ArrayMaths(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        double[] coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
        this.transformedGradient = coeff[1];

        // Adust mean and standard deviation of the transformed data to match those of the entered data
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Examples of flanagan.analysis.Regression.linear()

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        // Calculate Gaussian N[0,1] order statistic medians
        this.gaussianOrderMedians = Stat.gaussianOrderStatisticMedians(this.nData);

        // calculate the correlation coefficient of the probability plot for the untransformed data
        Regression reg = new Regression(this.gaussianOrderMedians, ((new ArrayMaths(this.standardizedOriginalData)).sort().array()));
        reg.linear();
        this.originalSampleR = reg.getSampleR();
        double[] coeff = reg.getBestEstimates();
        this.originalIntercept = coeff[0];
        this.originalGradient = coeff[1];
        coeff = reg.getBestEstimatesErrors();
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Examples of flanagan.analysis.Regression.linear()

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        // Obtain the intercept and gradient of the Gaussian probabilty plot
        ArrayMaths st4 = new ArrayMaths(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
        this.transformedGradient = coeff[1];
        coeff = reg.getBestEstimatesErrors();
        this.transformedInterceptError = coeff[0];
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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        // Calculate Gaussian N[0,1] order statistic medians
        this.gaussianOrderMedians = Stat.gaussianOrderStatisticMedians(this.nData);

        // calculate the correlation coefficient of the probability plot for the untransformed data
        Regression reg = new Regression(this.gaussianOrderMedians, ((new ArrayMaths(this.standardizedOriginalData)).sort().array()));
        reg.linear();
        this.originalSampleR = reg.getSampleR();
        double[] coeff = reg.getBestEstimates();
        this.originalIntercept = coeff[0];
        this.originalGradient = coeff[1];
        coeff = reg.getBestEstimatesErrors();
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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        // Obtain the intercept and gradient of the Gaussian probabilty plot
        Stat st4 = new Stat(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
        this.transformedGradient = coeff[1];
        coeff = reg.getBestEstimatesErrors();
        this.transformedInterceptError = coeff[0];
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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        // Obtain the intercept and gradient of the Gaussian probabilty plot
        Stat st4 = new Stat(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        double[] coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
        this.transformedGradient = coeff[1];

        // Adust mean and standard deviation of the transformed data to match those of the entered data
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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            xArray[i] = (resultFileSize / factor) * 100.0;
            yArray[i] = ((INumericValue)elapsedTimeMeasurements.getList().get(i).getValue()).value();
        }
       
        Regression reg = new Regression(xArray, yArray);
        reg.linear();
        double[] bestEstimates = reg.getBestEstimates();
       
        // y = k*x + d
        // y = bestEstimate[1]*x + bestEstimate[0]
        double startUpTime = bestEstimates[0];
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Examples of flanagan.analysis.Regression.linear()

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        // Calculate Gaussian N[0,1] order statistic medians
        this.gaussianOrderMedians = Stat.gaussianOrderStatisticMedians(this.nData);

        // calculate the correlation coefficient of the probability plot for the untransformed data
        Regression reg = new Regression(this.gaussianOrderMedians, ((new ArrayMaths(this.standardizedOriginalData)).sort().array()));
        reg.linear();
        this.originalSampleR = reg.getSampleR();
        double[] coeff = reg.getBestEstimates();
        this.originalIntercept = coeff[0];
        this.originalGradient = coeff[1];
    }
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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        // Obtain the intercept and gradient of the Gaussian probabilty plot
        Stat st4 = new Stat(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
        this.transformedGradient = coeff[1];

        // Adust mean and standard deviation of the transformed data to match those of the entered data
View Full Code Here

Examples of flanagan.analysis.Regression.linear()

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            xArray[i] = (resultFileSize / factor) * 100.0;
            yArray[i] = ((INumericValue) elapsedTimeMeasurements.getList().get(i).getValue()).value();
        }

        Regression reg = new Regression(xArray, yArray);
        reg.linear();
        double[] bestEstimates = reg.getBestEstimates();

        // y = k*x + d
        // y = bestEstimate[1]*x + bestEstimate[0]
        double startUpTime = bestEstimates[0];
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