/** * Creates a shallow copy of another target-estimate pair. * * @param other * TargetEstimatePair to shallow copy. */ public DefaultTargetEstimatePair( final Pair<? extends TargetType, ? extends EstimateType> other) { this(other.getFirst(), other.getSecond()); }
@Override public UniformDistribution.PDF learn( final Collection<? extends Double> data) { Pair<Double,Double> result = UnivariateStatisticsUtil.computeMinAndMax(data); final double min = result.getFirst(); final double max = result.getSecond(); final int k = data.size(); double a = min - Math.abs(min/k); double b = max + Math.abs(max/k); return new UniformDistribution.PDF( a, b ); }
@Override public UniformIntegerDistribution.PMF learn( final Collection<? extends Number> data) { final Pair<Double,Double> result = UnivariateStatisticsUtil.computeMinAndMax(data); final int min = result.getFirst().intValue(); final int max = result.getSecond().intValue(); return new UniformIntegerDistribution.PMF(min, max); }
@Override public ConfidenceInterval computeConfidenceInterval( Collection<? extends Number> data, double confidence ) { final Pair<Double,Double> meanAndVariance = UnivariateStatisticsUtil.computeMeanAndVariance(data); final double mean = meanAndVariance.getFirst(); final double variance = meanAndVariance.getSecond(); return computeConfidenceInterval( mean, variance, data.size(), confidence); }
@Override public GammaDistribution learn( final Collection<? extends WeightedValue<? extends Double>> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeWeightedMeanAndVariance(data); return MomentMatchingEstimator.learn( pair.getFirst(), pair.getSecond()); }
@Override public BetaDistribution learn( final Collection<? extends Double> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeMeanAndVariance(data); return learn( pair.getFirst(), pair.getSecond() ); }
/** * Copy constructor. * @param other Pair to copy. */ public DefaultPair( final Pair<? extends FirstType,? extends SecondType> other ) { this.setFirst(other.getFirst()); this.setSecond(other.getSecond()); }
@Override public GammaDistribution learn( final Collection<? extends Double> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeMeanAndVariance(data); return learn( pair.getFirst(), pair.getSecond() ); }
@Override public BetaDistribution learn( final Collection<? extends WeightedValue<? extends Double>> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeWeightedMeanAndVariance(data); return MomentMatchingEstimator.learn( pair.getFirst(), pair.getSecond() ); }
@Override public GammaDistribution learn( final Collection<? extends WeightedValue<? extends Double>> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeWeightedMeanAndVariance(data); return MomentMatchingEstimator.learn( pair.getFirst(), pair.getSecond()); }
@Override public GammaDistribution learn( final Collection<? extends WeightedValue<? extends Double>> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeWeightedMeanAndVariance(data); return MomentMatchingEstimator.learn( pair.getFirst(), pair.getSecond()); }
@Override public BetaDistribution learn( final Collection<? extends Double> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeMeanAndVariance(data); return learn( pair.getFirst(), pair.getSecond() ); }
@Override public GammaDistribution learn( final Collection<? extends Double> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeMeanAndVariance(data); return learn( pair.getFirst(), pair.getSecond() ); }
@Override public BetaDistribution learn( final Collection<? extends Double> data) { Pair<Double,Double> pair = UnivariateStatisticsUtil.computeMeanAndVariance(data); return learn( pair.getFirst(), pair.getSecond() ); }
@Override public Double call() throws Exception { ArrayList<? extends Double> means = this.t.sample( this.random, this.treatmentCount ); Pair<Double,Double> result = UnivariateStatisticsUtil.computeMinAndMax(means); double delta = result.getSecond() - result.getFirst(); means = null; return delta; }
public boolean equals( final Pair<FirstType, SecondType> other) { return other != null && ObjectUtil.equalsSafe(this.getFirst(), other.getFirst()) && ObjectUtil.equalsSafe(this.getSecond(), other.getSecond()); }
public boolean equals( final Pair<FirstType, SecondType> other) { return other != null && ObjectUtil.equalsSafe(this.getFirst(), other.getFirst()) && ObjectUtil.equalsSafe(this.getSecond(), other.getSecond()); }
public void toCogxels( PairType data, CogxelState cogxels ) { this.getFirstConverter().toCogxels( data.getFirst(), cogxels); this.getSecondConverter().toCogxels( data.getSecond(), cogxels); }
public void toCogxels( PairType data, CogxelState cogxels ) { this.getFirstConverter().toCogxels( data.getFirst(), cogxels); this.getSecondConverter().toCogxels( data.getSecond(), cogxels); }