Package | Description |
---|---|
org.hipparchus.distribution.continuous |
Implementations of common continuous distributions.
|
org.hipparchus.random |
Random number and random data generators.
|
org.hipparchus.samples | |
org.hipparchus.stat.fitting |
Statistical methods for fitting distributions.
|
org.hipparchus.stat.inference |
Classes providing hypothesis testing.
|
Modifier and Type | Class | Description |
---|---|---|
class |
AbstractRealDistribution |
Base class for probability distributions on the reals.
|
class |
BetaDistribution |
Implements the Beta distribution.
|
class |
CauchyDistribution |
Implementation of the Cauchy distribution.
|
class |
ChiSquaredDistribution |
Implementation of the chi-squared distribution.
|
class |
ConstantRealDistribution |
Implementation of the constant real distribution.
|
class |
EnumeratedRealDistribution |
Implementation of a real-valued
EnumeratedDistribution . |
class |
ExponentialDistribution |
Implementation of the exponential distribution.
|
class |
FDistribution |
Implementation of the F-distribution.
|
class |
GammaDistribution |
Implementation of the Gamma distribution.
|
class |
GumbelDistribution |
This class implements the Gumbel distribution.
|
class |
LaplaceDistribution |
This class implements the Laplace distribution.
|
class |
LevyDistribution |
This class implements the
Lévy distribution.
|
class |
LogisticDistribution |
This class implements the Logistic distribution.
|
class |
LogNormalDistribution |
Implementation of the log-normal (gaussian) distribution.
|
class |
NakagamiDistribution |
This class implements the Nakagami distribution.
|
class |
NormalDistribution |
Implementation of the normal (gaussian) distribution.
|
class |
ParetoDistribution |
Implementation of the Pareto distribution.
|
class |
TDistribution |
Implementation of Student's t-distribution.
|
class |
TriangularDistribution |
Implementation of the triangular real distribution.
|
class |
UniformRealDistribution |
Implementation of the uniform real distribution.
|
class |
WeibullDistribution |
Implementation of the Weibull distribution.
|
Modifier and Type | Method | Description |
---|---|---|
double |
RandomDataGenerator.nextDeviate(RealDistribution dist) |
Returns a random deviate from the given distribution.
|
double[] |
RandomDataGenerator.nextDeviates(RealDistribution dist,
int size) |
Returns an array of random deviates from the given distribution.
|
Modifier and Type | Method | Description |
---|---|---|
static void |
RealDistributionComparison.addCDFSeries(com.xeiam.xchart.Chart chart,
RealDistribution distribution,
String desc,
int lowerBound,
int upperBound) |
|
static void |
RealDistributionComparison.addPDFSeries(com.xeiam.xchart.Chart chart,
RealDistribution distribution,
String desc,
int lowerBound,
int upperBound) |
|
static JComponent |
RealDistributionComparison.createComponent(String distributionName,
int minX,
int maxX,
String[] seriesText,
RealDistribution... series) |
Modifier and Type | Class | Description |
---|---|---|
class |
EmpiricalDistribution |
Represents an
empirical probability distribution -- a probability distribution derived
from observed data without making any assumptions about the functional form
of the population distribution that the data come from.
|
Modifier and Type | Method | Description |
---|---|---|
protected RealDistribution |
EmpiricalDistribution.getKernel(StreamingStatistics bStats) |
The within-bin smoothing kernel.
|
Modifier and Type | Method | Description |
---|---|---|
static double |
InferenceTestUtils.kolmogorovSmirnovStatistic(RealDistribution dist,
double[] data) |
|
double |
KolmogorovSmirnovTest.kolmogorovSmirnovStatistic(RealDistribution distribution,
double[] data) |
Computes the one-sample Kolmogorov-Smirnov test statistic, \(D_n=\sup_x |F_n(x)-F(x)|\) where
\(F\) is the distribution (cdf) function associated with
distribution , \(n\) is the
length of data and \(F_n\) is the empirical distribution that puts mass \(1/n\) at
each of the values in data . |
static double |
InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist,
double[] data) |
|
static double |
InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist,
double[] data,
boolean strict) |
|
static boolean |
InferenceTestUtils.kolmogorovSmirnovTest(RealDistribution dist,
double[] data,
double alpha) |
|
double |
KolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution,
double[] data) |
Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test
evaluating the null hypothesis that
data conforms to distribution . |
double |
KolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution,
double[] data,
boolean exact) |
Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test
evaluating the null hypothesis that
data conforms to distribution . |
boolean |
KolmogorovSmirnovTest.kolmogorovSmirnovTest(RealDistribution distribution,
double[] data,
double alpha) |
Performs a Kolmogorov-Smirnov
test evaluating the null hypothesis that
data conforms to distribution . |
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