Uses of Interface
org.apache.commons.statistics.descriptive.StatisticResult

Packages that use StatisticResult

Package	Description
org.apache.commons.statistics.descriptive	Implementations of univariate statistics.

Uses of StatisticResult in org.apache.commons.statistics.descriptive

Classes in org.apache.commons.statistics.descriptive with type parameters of type StatisticResult

Modifier and Type	Interface	Description
interface	StatisticAccumulator<T extends StatisticResult>	A mutable result container that accumulates a StatisticResult.

Subinterfaces of StatisticResult in org.apache.commons.statistics.descriptive

Modifier and Type	Interface	Description
(package private) interface	BigIntegerStatisticResult	Represents the BigInteger result of a statistic computed over a set of values.
interface	DoubleStatistic	Represents a state object for computing a statistic over double valued input(s).
interface	IntStatistic	Represents a state object for computing a statistic over int valued input(s).
(package private) interface	IntStatisticResult	Represents the int result of a statistic computed over a set of values.
interface	LongStatistic	Represents a state object for computing a statistic over long valued input(s).
(package private) interface	LongStatisticResult	Represents the long result of a statistic computed over a set of values.

Classes in org.apache.commons.statistics.descriptive that implement StatisticResult

Modifier and Type	Class	Description
final class	GeometricMean	Computes the geometric mean of the available values.
final class	IntMax	Returns the maximum of the available values.
final class	IntMean	Computes the arithmetic mean of the available values.
final class	IntMin	Returns the minimum of the available values.
final class	IntStandardDeviation	Computes the standard deviation of the available values.
final class	IntSum	Returns the sum of the available values.
final class	IntSumOfSquares	Returns the sum of the squares of the available values.
final class	IntVariance	Computes the variance of the available values.
final class	Kurtosis	Computes the kurtosis of the available values.
final class	LongMax	Returns the maximum of the available values.
final class	LongMean	Computes the arithmetic mean of the available values.
final class	LongMin	Returns the minimum of the available values.
final class	LongStandardDeviation	Computes the standard deviation of the available values.
final class	LongSum	Returns the sum of the available values.
final class	LongSumOfSquares	Returns the sum of the squares of the available values.
final class	LongVariance	Computes the variance of the available values.
final class	Max	Returns the maximum of the available values.
final class	Mean	Computes the arithmetic mean of the available values.
final class	Min	Returns the minimum of the available values.
final class	Product	Returns the product of the available values.
final class	Skewness	Computes the skewness of the available values.
final class	StandardDeviation	Computes the standard deviation of the available values.
final class	Sum	Returns the sum of the available values.
final class	SumOfLogs	Returns the sum of the natural logarithm of available values.
final class	SumOfSquares	Returns the sum of the squares of the available values.
final class	Variance	Computes the variance of the available values.

Methods in org.apache.commons.statistics.descriptive with type parameters of type StatisticResult

Modifier and Type	Method	Description
(package private) static <T extends StatisticResult & StatisticAccumulator<T>> void	Statistics.checkCombineCompatible(T a, T b)	Check left-hand side argument a is null or else the right-hand side argument b must also be non-null so the statistics can be combined.
(package private) static <T extends StatisticResult & StatisticAccumulator<T>> void	Statistics.combine(T a, T b)	If the left-hand side argument a is non-null, combine it with the right-hand side argument b.

Methods in org.apache.commons.statistics.descriptive that return StatisticResult

Modifier and Type	Method	Description
private StatisticResult	Median.compute(long[] values, int from, int to)	Compute the median of the specified range.
private StatisticResult	Quantile.compute(long[] values, int from, int to, double p)	Compute the p-th quantile of the specified range of values.
private StatisticResult[]	Quantile.compute(long[] values, int from, int to, double... p)	Evaluate the p-th quantiles of the specified range of values..
(package private) static StatisticResult	Statistics.createStatisticResult(long value)	Creates the statistic result using a long value.
StatisticResult	Median.evaluate(long[] values)	Evaluate the median.
StatisticResult	Quantile.evaluate(long[] values, double p)	Evaluate the p-th quantile of the values.
StatisticResult[]	Quantile.evaluate(long[] values, double... p)	Evaluate the p-th quantiles of the values.
StatisticResult	Quantile.evaluateAsLong(int n, IntToLongFunction values, double p)	Evaluate the p-th quantile of the sorted values provided as a long.
StatisticResult[]	Quantile.evaluateAsLong(int n, IntToLongFunction values, double... p)	Evaluate the p-th quantiles of the sorted values provided as a long.
StatisticResult	Median.evaluateRange(long[] values, int from, int to)	Evaluate the median of the specified range.
StatisticResult	Quantile.evaluateRange(long[] values, int from, int to, double p)	Evaluate the p-th quantile of the specified range of values.
StatisticResult[]	Quantile.evaluateRange(long[] values, int from, int to, double... p)	Evaluate the p-th quantiles of the specified range of values..
private StatisticResult	DoubleStatistics.getGeometricMean()	Gets the geometric mean.
private StatisticResult	IntStatistics.getGeometricMean()	Gets the geometric mean.
private StatisticResult	LongStatistics.getGeometricMean()	Gets the geometric mean.
private StatisticResult	DoubleStatistics.getKurtosis()	Gets the kurtosis.
private StatisticResult	IntStatistics.getKurtosis()	Gets the kurtosis.
private StatisticResult	LongStatistics.getKurtosis()	Gets the kurtosis.
private StatisticResult	DoubleStatistics.getMean()	Gets the mean.
private StatisticResult	IntStatistics.getMean()	Gets the mean.
private StatisticResult	LongStatistics.getMean()	Gets the mean.
StatisticResult	DoubleStatistics.getResult(Statistic statistic)	Gets a supplier for the value of the specified statistic.
StatisticResult	IntStatistics.getResult(Statistic statistic)	Gets a supplier for the value of the specified statistic.
StatisticResult	LongStatistics.getResult(Statistic statistic)	Gets a supplier for the value of the specified statistic.
(package private) static StatisticResult	Statistics.getResultAsBigIntegerOrNull(StatisticResult s)	Gets the statistic result using the BigInteger value.
(package private) static StatisticResult	Statistics.getResultAsDoubleOrNull(StatisticResult s)	Gets the statistic result using the double value.
(package private) static StatisticResult	Statistics.getResultAsIntOrNull(StatisticResult s)	Gets the statistic result using the int value.
(package private) static StatisticResult	Statistics.getResultAsLongOrNull(StatisticResult s)	Gets the statistic result using the long value.
private StatisticResult	DoubleStatistics.getSkewness()	Gets the skewness.
private StatisticResult	IntStatistics.getSkewness()	Gets the skewness.
private StatisticResult	LongStatistics.getSkewness()	Gets the skewness.
private StatisticResult	DoubleStatistics.getStandardDeviation()	Gets the standard deviation.
private StatisticResult	IntStatistics.getStandardDeviation()	Gets the standard deviation.
private StatisticResult	LongStatistics.getStandardDeviation()	Gets the standard deviation.
private StatisticResult	DoubleStatistics.getVariance()	Gets the variance.
private StatisticResult	IntStatistics.getVariance()	Gets the variance.
private StatisticResult	LongStatistics.getVariance()	Gets the variance.
private StatisticResult	IntStatistics.getVarianceOrStd(boolean std)	Gets the variance or standard deviation.
private StatisticResult	LongStatistics.getVarianceOrStd(boolean std)	Gets the variance or standard deviation.
(package private) static StatisticResult	Interpolation.interpolate(long a, long b, double t)	Linear interpolation between sorted values a <= b using the interpolant t.
(package private) static StatisticResult	Interpolation.mean(long x, long y)	Compute the arithmetic mean of the two values.

Methods in org.apache.commons.statistics.descriptive with parameters of type StatisticResult

Modifier and Type	Method	Description
(package private) static StatisticResult	Statistics.getResultAsBigIntegerOrNull(StatisticResult s)	Gets the statistic result using the BigInteger value.
(package private) static StatisticResult	Statistics.getResultAsDoubleOrNull(StatisticResult s)	Gets the statistic result using the double value.
(package private) static StatisticResult	Statistics.getResultAsIntOrNull(StatisticResult s)	Gets the statistic result using the int value.
(package private) static StatisticResult	Statistics.getResultAsLongOrNull(StatisticResult s)	Gets the statistic result using the long value.