Enum BinomialConfidenceInterval
java.lang.Object
java.lang.Enum<BinomialConfidenceInterval>
org.apache.commons.statistics.interval.BinomialConfidenceInterval
- All Implemented Interfaces:
Serializable, Comparable<BinomialConfidenceInterval>
Generate confidence intervals for a binomial proportion.
Note: To avoid overshoot, the confidence intervals are clipped to be in the
[0, 1] interval in the case of the normal
approximation and Agresti-Coull methods.
- Since:
- 1.2
- See Also:
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Enum Constant Summary
Enum ConstantsEnum ConstantDescriptionImplements the Agresti-Coull method for creating a binomial proportion confidence interval.Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.Implements the Jeffreys method for creating a binomial proportion confidence interval.Implements the normal approximation method for creating a binomial proportion confidence interval.Implements the Wilson score method for creating a binomial proportion confidence interval. -
Field Summary
FieldsModifier and TypeFieldDescription(package private) static final NormalDistributionThe standard normal distribution. -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescription(package private) static doubleclip(double p) Clip the probability to [0, 1].(package private) abstract Intervalcreate(int n, int x, double alpha) Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and error rate.fromErrorRate(int numberOfTrials, int numberOfSuccesses, double alpha) Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and error rate.static BinomialConfidenceIntervalReturns the enum constant of this type with the specified name.static BinomialConfidenceInterval[]values()Returns an array containing the constants of this enum type, in the order they are declared.
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Enum Constant Details
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NORMAL_APPROXIMATION
Implements the normal approximation method for creating a binomial proportion confidence interval.This method clips the confidence interval to be in
[0, 1].- See Also:
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WILSON_SCORE
Implements the Wilson score method for creating a binomial proportion confidence interval.- See Also:
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JEFFREYS
Implements the Jeffreys method for creating a binomial proportion confidence interval.In order to avoid the coverage probability tending to zero when
ptends towards 0 or 1, whenx = 0the lower limit is set to 0, and whenx = nthe upper limit is set to 1.- See Also:
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CLOPPER_PEARSON
Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.- See Also:
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AGRESTI_COULL
Implements the Agresti-Coull method for creating a binomial proportion confidence interval.This method clips the confidence interval to be in
[0, 1].- See Also:
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Field Details
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NORMAL_DISTRIBUTION
The standard normal distribution.
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Constructor Details
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BinomialConfidenceInterval
private BinomialConfidenceInterval()
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Method Details
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values
Returns an array containing the constants of this enum type, in the order they are declared.- Returns:
- an array containing the constants of this enum type, in the order they are declared
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valueOf
Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)- Parameters:
name- the name of the enum constant to be returned.- Returns:
- the enum constant with the specified name
- Throws:
IllegalArgumentException- if this enum type has no constant with the specified nameNullPointerException- if the argument is null
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fromErrorRate
Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and error rate.The error rate
alphais related to the confidence level that the interval contains the true probability of success asalpha = 1 - confidence, whereconfidenceis the confidence level in[0, 1]. For example a 95% confidence level is analphaof 0.05.- Parameters:
numberOfTrials- Number of trials.numberOfSuccesses- Number of successes.alpha- Desired error rate that the true probability of success falls outside the returned interval.- Returns:
- Confidence interval containing the probability of success with error rate
alpha - Throws:
IllegalArgumentException- ifnumberOfTrials <= 0, ifnumberOfSuccesses < 0, ifnumberOfSuccesses > numberOfTrials, or ifalphais not in the open interval(0, 1).
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create
Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and error rate.- Parameters:
n- Number of trials.x- Number of successes.alpha- Desired error rate.- Returns:
- Confidence interval
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clip
static double clip(double p) Clip the probability to [0, 1].- Parameters:
p- Probability.- Returns:
- the probability in [0, 1]
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