@PublicationReference(author="Wikipedia", title="Markov\'s Inequality", type=WebPage, year=2009, url="http://en.wikipedia.org/wiki/Markov%27s_inequality") public class MarkovInequality extends AbstractCloneableSerializable implements ConfidenceIntervalEvaluator<java.util.Collection<java.lang.Double>>
Modifier and Type | Field and Description |
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static MarkovInequality |
INSTANCE
This class has no members, so here's a static instance.
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Constructor and Description |
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MarkovInequality()
Creates a new instance of MarkovInequality
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Modifier and Type | Method and Description |
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ConfidenceInterval |
computeConfidenceInterval(java.util.Collection<java.lang.Double> data,
double confidence)
Computes the Markov Inequality Bound for the given data at the
given confidence level.
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ConfidenceInterval |
computeConfidenceInterval(double mean,
double variance,
int numSamples,
double confidence)
Computes the confidence interval given the mean and variance of
the samples, number of samples, and corresponding confidence interval
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static ConfidenceInterval |
computeConfidenceInterval(double sampleMean,
int numSamples,
double confidence)
Computes the Markov Inequality Bound for the given data at the
given confidence level.
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clone
public static final MarkovInequality INSTANCE
public MarkovInequality()
public ConfidenceInterval computeConfidenceInterval(java.util.Collection<java.lang.Double> data, double confidence)
computeConfidenceInterval
in interface ConfidenceIntervalEvaluator<java.util.Collection<java.lang.Double>>
data
- Values drawn from the underlying distributionconfidence
- Confidence value to find the range of values forpublic static ConfidenceInterval computeConfidenceInterval(double sampleMean, int numSamples, double confidence)
sampleMean
- Sample mean of the underlying datanumSamples
- Number of samples used in computing the meanconfidence
- Confidence value to find the range of values forpublic ConfidenceInterval computeConfidenceInterval(double mean, double variance, int numSamples, double confidence)
ConfidenceIntervalEvaluator
computeConfidenceInterval
in interface ConfidenceIntervalEvaluator<java.util.Collection<java.lang.Double>>
mean
- Mean of the distribution.variance
- Variance of the distribution.numSamples
- Number of samples in the underlying dataconfidence
- Confidence value to assume for the ConfidenceInterval