Examples of org.apache.commons.math3.distribution.NormalDistribution.cumulativeProbability()

Package org.apache.commons.math3.distribution

Class org.apache.commons.math3.distribution.NormalDistribution

Examples of org.apache.commons.math3.distribution.NormalDistribution.cumulativeProbability()

org.apache.commons.math3.distribution.NormalDistribution.cumulativeProbability()
{@inheritDoc}If {@code x} is more than 40 standard deviations from the mean, 0 or 1is returned, as in these cases the actual value is within {@code Double.MIN_VALUE} of 0 or 1.

            final long[] observed2)
            throws DimensionMismatchException, NotPositiveException, ZeroException,
            MaxCountExceededException {
        final ChiSquaredDistribution distribution = new ChiSquaredDistribution(
                (double) observed1.length - 1);
        return 1 - distribution.cumulativeProbability(
                gDataSetsComparison(observed1, observed2));
    }


    /**
     * <p>Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned

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        final AnovaStats a = anovaStats(categoryData);
        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);


    }


    /**
     * Computes the ANOVA P-value for a collection of {@link SummaryStatistics}.

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               ConvergenceException, MaxCountExceededException {


        final AnovaStats a = anovaStats(categoryData, allowOneElementData);
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);


    }


    /**
     * This method calls the method that actually does the calculations (except

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        throws NullArgumentException, DimensionMismatchException,
        ConvergenceException, MaxCountExceededException {


        AnovaStats a = anovaStats(categoryData);
        FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);


    }


    /**
     * Performs an ANOVA test, evaluating the null hypothesis that there

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        ConvergenceException, MaxCountExceededException {


        AnovaStats a = anovaStats(categoryData);
        // No try-catch or advertised exception because args are valid
        FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);


    }


    /**
     * Computes the ANOVA P-value for a collection of {@link SummaryStatistics}.

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        throws NullArgumentException, DimensionMismatchException,
               ConvergenceException, MaxCountExceededException {


        final AnovaStats a = anovaStats(categoryData, allowOneElementData);
        final FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);


    }


    /**
     * This method calls the method that actually does the calculations (except

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        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final NormalDistribution standardNormal = new NormalDistribution(null, 0, 1);


        return 2*standardNormal.cumulativeProbability(z);
    }


    /**
     * Returns the <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">

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        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final NormalDistribution standardNormal = new NormalDistribution(null, 0, 1);


        return 2 * standardNormal.cumulativeProbability(z);
    }


    /**
     * Returns the asymptotic <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">

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        final double z = (Umin - EU) / FastMath.sqrt(VarU);


        final NormalDistribution standardNormal = new NormalDistribution(0, 1);


        return 2 * standardNormal.cumulativeProbability(z);
    }


    /**
     * Returns the asymptotic <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">

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        // - 0.5 is a continuity correction
        final double z = (Wmin - ES - 0.5) / FastMath.sqrt(VarS);


        final NormalDistribution standardNormal = new NormalDistribution(0, 1);


        return 2*standardNormal.cumulativeProbability(z);
    }


    /**
     * Returns the <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">

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