Uses of Interface org.hipparchus.stat.descriptive.StatisticalSummary (Hipparchus 3.0 API)

Packages that use StatisticalSummary
Package	Description
org.hipparchus.stat.descriptive	Generic univariate and multivariate summary statistic objects.
org.hipparchus.stat.fitting	Statistical methods for fitting distributions.
org.hipparchus.stat.inference	Classes providing hypothesis testing.

Uses of StatisticalSummary in org.hipparchus.stat.descriptive

Classes in org.hipparchus.stat.descriptive that implement StatisticalSummary
Modifier and Type	Class	Description
`class`	`DescriptiveStatistics`	Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
`class`	`StatisticalSummaryValues`	Value object representing the results of a univariate statistical summary.
`class`	`StreamingStatistics`	Computes summary statistics for a stream of data values added using the `addValue` method.

Methods in org.hipparchus.stat.descriptive that return StatisticalSummary
Modifier and Type	Method	Description
`static StatisticalSummary`	StatisticalSummary.`aggregate(Iterable<? extends StatisticalSummary> statistics)`	Computes aggregated statistical summaries.
`static StatisticalSummary`	StatisticalSummary.`aggregate(StatisticalSummary... statistics)`	Computes aggregated statistical summaries.
`StatisticalSummary`	StreamingStatistics.`getSummary()`	Return a `StatisticalSummaryValues` instance reporting current statistics.

Methods in org.hipparchus.stat.descriptive with parameters of type StatisticalSummary
Modifier and Type	Method	Description
`static StatisticalSummary`	StatisticalSummary.`aggregate(StatisticalSummary... statistics)`	Computes aggregated statistical summaries.

Method parameters in org.hipparchus.stat.descriptive with type arguments of type StatisticalSummary
Modifier and Type	Method	Description
`static StatisticalSummary`	StatisticalSummary.`aggregate(Iterable<? extends StatisticalSummary> statistics)`	Computes aggregated statistical summaries.

Uses of StatisticalSummary in org.hipparchus.stat.fitting

Methods in org.hipparchus.stat.fitting that return StatisticalSummary
Modifier and Type	Method	Description
`StatisticalSummary`	EmpiricalDistribution.`getSampleStats()`	Returns a `StatisticalSummary` describing this distribution.

Uses of StatisticalSummary in org.hipparchus.stat.inference

Methods in org.hipparchus.stat.inference with parameters of type StatisticalSummary
Modifier and Type	Method	Description
`static double`	InferenceTestUtils.`homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
`double`	TTest.`homoscedasticT(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
`static double`	InferenceTestUtils.`homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
`double`	TTest.`homoscedasticTTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
`static double`	InferenceTestUtils.`t(double mu, StatisticalSummary sampleStats)`	Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
`static double`	InferenceTestUtils.`t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
`double`	TTest.`t(double mu, StatisticalSummary sampleStats)`	Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
`double`	TTest.`t(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
`static double`	InferenceTestUtils.`tTest(double mu, StatisticalSummary sampleStats)`	Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
`static boolean`	InferenceTestUtils.`tTest(double mu, StatisticalSummary sampleStats, double alpha)`	Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
`static double`	InferenceTestUtils.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
`static boolean`	InferenceTestUtils.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)`	Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.
`double`	TTest.`tTest(double mu, StatisticalSummary sampleStats)`	Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
`boolean`	TTest.`tTest(double mu, StatisticalSummary sampleStats, double alpha)`	Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
`double`	TTest.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2)`	Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
`boolean`	TTest.`tTest(StatisticalSummary sampleStats1, StatisticalSummary sampleStats2, double alpha)`	Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.