| Package | Description |
|---|---|
| org.apache.commons.math3.analysis |
Parent package for common numerical analysis procedures, including root finding,
function interpolation and integration.
|
| org.apache.commons.math3.analysis.differentiation |
This package holds the main interfaces and basic building block classes
dealing with differentiation.
|
| org.apache.commons.math3.analysis.integration |
Numerical integration (quadrature) algorithms for univariate real functions.
|
| org.apache.commons.math3.analysis.solvers |
Root finding algorithms, for univariate real functions.
|
| org.apache.commons.math3.distribution |
Implementations of common discrete and continuous distributions.
|
| org.apache.commons.math3.genetics |
This package provides Genetic Algorithms components and implementations.
|
| org.apache.commons.math3.geometry.spherical.oned |
This package provides basic geometry components on the 1-sphere.
|
| org.apache.commons.math3.linear |
Linear algebra support.
|
| org.apache.commons.math3.random |
Random number and random data generators.
|
| org.apache.commons.math3.special |
Implementations of special functions such as Beta and Gamma.
|
| org.apache.commons.math3.stat.inference |
Classes providing hypothesis testing.
|
| org.apache.commons.math3.stat.interval |
Classes providing binomial proportion confidence interval construction.
|
| org.apache.commons.math3.util |
Convenience routines and common data structures used throughout the commons-math library.
|
| Modifier and Type | Method and Description |
|---|---|
static double[] |
FunctionUtils.sample(UnivariateFunction f,
double min,
double max,
int n)
Samples the specified univariate real function on the specified interval.
|
| Modifier and Type | Method and Description |
|---|---|
static DSCompiler |
DSCompiler.getCompiler(int parameters,
int order)
Get the compiler for number of free parameters and order.
|
double |
DerivativeStructure.getPartialDerivative(int... orders)
Get a partial derivative.
|
int |
DSCompiler.getPartialDerivativeIndex(int... orders)
Get the index of a partial derivative in the array.
|
| Constructor and Description |
|---|
DerivativeStructure(int parameters,
int order)
Build an instance with all values and derivatives set to 0.
|
DerivativeStructure(int parameters,
int order,
double... derivatives)
Build an instance from all its derivatives.
|
DerivativeStructure(int parameters,
int order,
double value)
Build an instance representing a constant value.
|
DerivativeStructure(int parameters,
int order,
int index,
double value)
Build an instance representing a variable.
|
FiniteDifferencesDifferentiator(int nbPoints,
double stepSize,
double tLower,
double tUpper)
Build a differentiator with number of points and step size when independent variable is bounded.
|
| Constructor and Description |
|---|
MidPointIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a midpoint integrator with given accuracies and iterations counts.
|
MidPointIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a midpoint integrator with given iteration counts.
|
RombergIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given accuracies and iterations counts.
|
RombergIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given iteration counts.
|
SimpsonIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a Simpson integrator with given accuracies and iterations counts.
|
SimpsonIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a Simpson integrator with given iteration counts.
|
TrapezoidIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a trapezoid integrator with given accuracies and iterations counts.
|
TrapezoidIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a trapezoid integrator with given iteration counts.
|
| Modifier and Type | Method and Description |
|---|---|
double |
LaguerreSolver.doSolve()
Method for implementing actual optimization algorithms in derived
classes.
|
protected double |
BrentSolver.doSolve()
Method for implementing actual optimization algorithms in derived
classes.
|
protected double |
BracketingNthOrderBrentSolver.doSolve()
Method for implementing actual optimization algorithms in derived
classes.
|
protected double |
MullerSolver.doSolve()
Method for implementing actual optimization algorithms in derived
classes.
|
protected double |
MullerSolver2.doSolve()
Method for implementing actual optimization algorithms in derived
classes.
|
double |
BracketingNthOrderBrentSolver.solve(int maxEval,
UnivariateFunction f,
double min,
double max,
AllowedSolution allowedSolution)
Solve for a zero in the given interval.
|
double |
BracketingNthOrderBrentSolver.solve(int maxEval,
UnivariateFunction f,
double min,
double max,
double startValue,
AllowedSolution allowedSolution)
Solve for a zero in the given interval, start at
startValue. |
static void |
UnivariateSolverUtils.verifyInterval(double lower,
double upper)
Check that the endpoints specify an interval.
|
protected void |
BaseAbstractUnivariateSolver.verifyInterval(double lower,
double upper)
Check that the endpoints specify an interval.
|
static void |
UnivariateSolverUtils.verifySequence(double lower,
double initial,
double upper)
Check that
lower < initial < upper. |
protected void |
BaseAbstractUnivariateSolver.verifySequence(double lower,
double initial,
double upper)
Check that
lower < initial < upper. |
| Modifier and Type | Method and Description |
|---|---|
double |
LogNormalDistribution.cumulativeProbability(double x0,
double x1)
Deprecated.
|
double |
NormalDistribution.cumulativeProbability(double x0,
double x1)
Deprecated.
|
double |
ParetoDistribution.cumulativeProbability(double x0,
double x1)
Deprecated.
|
double |
RealDistribution.cumulativeProbability(double x0,
double x1)
Deprecated.
As of 3.1. In 4.0, this method will be renamed
probability(double x0, double x1). |
double |
AbstractRealDistribution.cumulativeProbability(double x0,
double x1)
Deprecated.
As of 3.1 (to be removed in 4.0). Please use
AbstractRealDistribution.probability(double,double) instead. |
double |
IntegerDistribution.cumulativeProbability(int x0,
int x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1). |
double |
AbstractIntegerDistribution.cumulativeProbability(int x0,
int x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1). |
double |
LogNormalDistribution.probability(double x0,
double x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1). |
double |
NormalDistribution.probability(double x0,
double x1)
For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1). |
| Constructor and Description |
|---|
HypergeometricDistribution(int populationSize,
int numberOfSuccesses,
int sampleSize)
Construct a new hypergeometric distribution with the specified population
size, number of successes in the population, and sample size.
|
HypergeometricDistribution(RandomGenerator rng,
int populationSize,
int numberOfSuccesses,
int sampleSize)
Creates a new hypergeometric distribution.
|
TriangularDistribution(double a,
double c,
double b)
Creates a triangular real distribution using the given lower limit,
upper limit, and mode.
|
TriangularDistribution(RandomGenerator rng,
double a,
double c,
double b)
Creates a triangular distribution.
|
UniformIntegerDistribution(int lower,
int upper)
Creates a new uniform integer distribution using the given lower and
upper bounds (both inclusive).
|
UniformIntegerDistribution(RandomGenerator rng,
int lower,
int upper)
Creates a new uniform integer distribution using the given lower and
upper bounds (both inclusive).
|
UniformRealDistribution(double lower,
double upper)
Create a uniform real distribution using the given lower and upper
bounds.
|
UniformRealDistribution(double lower,
double upper,
double inverseCumAccuracy)
Deprecated.
as of 3.2, inverse CDF is now calculated analytically, use
UniformRealDistribution.UniformRealDistribution(double, double) instead. |
UniformRealDistribution(RandomGenerator rng,
double lower,
double upper)
Creates a uniform distribution.
|
| Modifier and Type | Method and Description |
|---|---|
void |
Population.addChromosome(Chromosome chromosome)
Add the given chromosome to the population.
|
void |
ListPopulation.addChromosome(Chromosome chromosome)
Add the given chromosome to the population.
|
void |
ListPopulation.addChromosomes(Collection<Chromosome> chromosomeColl)
Add a
Collection of chromosomes to this Population. |
void |
ListPopulation.setChromosomes(List<Chromosome> chromosomes)
Deprecated.
use
ListPopulation.addChromosomes(Collection) instead |
| Constructor and Description |
|---|
ElitisticListPopulation(List<Chromosome> chromosomes,
int populationLimit,
double elitismRate)
Creates a new
ElitisticListPopulation instance. |
ListPopulation(List<Chromosome> chromosomes,
int populationLimit)
Creates a new ListPopulation instance.
|
| Constructor and Description |
|---|
Arc(double lower,
double upper,
double tolerance)
Simple constructor.
|
ArcsSet(double lower,
double upper,
double tolerance)
Build an arcs set corresponding to a single arc.
|
| Modifier and Type | Method and Description |
|---|---|
void |
DiagonalMatrix.addToEntry(int row,
int column,
double increment)
Adds (in place) the specified value to the specified entry of
this matrix. |
OpenMapRealMatrix |
OpenMapRealMatrix.createMatrix(int rowDimension,
int columnDimension)
Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
|
OpenMapRealMatrix |
OpenMapRealMatrix.multiply(OpenMapRealMatrix m)
Postmultiply this matrix by
m. |
RealMatrix |
OpenMapRealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying
this by m. |
void |
DiagonalMatrix.setEntry(int row,
int column,
double value)
Set the entry in the specified row and column.
|
| Constructor and Description |
|---|
ArrayFieldVector(Field<T> field,
T[] d,
int pos,
int size)
Construct a vector from part of a array.
|
ArrayFieldVector(T[] d,
int pos,
int size)
Construct a vector from part of a array.
|
ArrayRealVector(double[] d,
int pos,
int size)
Construct a vector from part of a array.
|
ArrayRealVector(Double[] d,
int pos,
int size)
Construct a vector from part of an array.
|
OpenMapRealMatrix(int rowDimension,
int columnDimension)
Build a sparse matrix with the supplied row and column dimensions.
|
| Modifier and Type | Method and Description |
|---|---|
int |
RandomDataGenerator.nextHypergeometric(int populationSize,
int numberOfSuccesses,
int sampleSize)
Generates a random value from the
Hypergeometric Distribution. |
int |
RandomDataImpl.nextHypergeometric(int populationSize,
int numberOfSuccesses,
int sampleSize)
Deprecated.
Generates a random value from the
Hypergeometric Distribution. |
int |
RandomDataGenerator.nextInt(int lower,
int upper)
Generates a uniformly distributed random integer between
lower
and upper (endpoints included). |
int |
RandomData.nextInt(int lower,
int upper)
Deprecated.
Generates a uniformly distributed random integer between
lower
and upper (endpoints included). |
int |
RandomDataImpl.nextInt(int lower,
int upper)
Deprecated.
Generates a uniformly distributed random integer between
lower
and upper (endpoints included). |
long |
RandomDataGenerator.nextLong(long lower,
long upper)
Generates a uniformly distributed random long integer between
lower and upper (endpoints included). |
long |
RandomData.nextLong(long lower,
long upper)
Deprecated.
Generates a uniformly distributed random long integer between
lower and upper (endpoints included). |
long |
RandomDataImpl.nextLong(long lower,
long upper)
Deprecated.
Generates a uniformly distributed random long integer between
lower and upper (endpoints included). |
int[] |
RandomDataGenerator.nextPermutation(int n,
int k)
Generates an integer array of length
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive). |
int[] |
RandomData.nextPermutation(int n,
int k)
Deprecated.
Generates an integer array of length
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive). |
int[] |
RandomDataImpl.nextPermutation(int n,
int k)
Deprecated.
Generates an integer array of length
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive). |
Object[] |
RandomDataGenerator.nextSample(Collection<?> c,
int k)
Returns an array of
k objects selected randomly from the
Collection c. |
Object[] |
RandomData.nextSample(Collection<?> c,
int k)
Deprecated.
Returns an array of
k objects selected randomly from the
Collection c. |
Object[] |
RandomDataImpl.nextSample(Collection<?> c,
int k)
Deprecated.
Returns an array of
k objects selected randomly from the
Collection c. |
int |
RandomDataGenerator.nextSecureInt(int lower,
int upper)
Generates a uniformly distributed random integer between
lower
and upper (endpoints included) from a secure random sequence. |
int |
RandomData.nextSecureInt(int lower,
int upper)
Deprecated.
Generates a uniformly distributed random integer between
lower
and upper (endpoints included) from a secure random sequence. |
int |
RandomDataImpl.nextSecureInt(int lower,
int upper)
Deprecated.
Generates a uniformly distributed random integer between
lower
and upper (endpoints included) from a secure random sequence. |
long |
RandomDataGenerator.nextSecureLong(long lower,
long upper)
Generates a uniformly distributed random long integer between
lower and upper (endpoints included) from a secure random
sequence. |
long |
RandomData.nextSecureLong(long lower,
long upper)
Deprecated.
Generates a uniformly distributed random long integer between
lower and upper (endpoints included) from a secure random
sequence. |
long |
RandomDataImpl.nextSecureLong(long lower,
long upper)
Deprecated.
Generates a uniformly distributed random long integer between
lower and upper (endpoints included) from a secure random
sequence. |
double |
RandomDataGenerator.nextUniform(double lower,
double upper)
Generates a uniformly distributed random value from the open interval
(lower, upper) (i.e., endpoints excluded). |
double |
RandomData.nextUniform(double lower,
double upper)
Deprecated.
Generates a uniformly distributed random value from the open interval
(lower, upper) (i.e., endpoints excluded). |
double |
RandomDataImpl.nextUniform(double lower,
double upper)
Deprecated.
Generates a uniformly distributed random value from the open interval
(lower, upper) (i.e., endpoints excluded). |
double |
RandomDataGenerator.nextUniform(double lower,
double upper,
boolean lowerInclusive)
Generates a uniformly distributed random value from the interval
(lower, upper) or the interval [lower, upper). |
double |
RandomData.nextUniform(double lower,
double upper,
boolean lowerInclusive)
Deprecated.
Generates a uniformly distributed random value from the interval
(lower, upper) or the interval [lower, upper). |
double |
RandomDataImpl.nextUniform(double lower,
double upper,
boolean lowerInclusive)
Deprecated.
Generates a uniformly distributed random value from the interval
(lower, upper) or the interval [lower, upper). |
| Modifier and Type | Method and Description |
|---|---|
static double |
Gamma.logGamma1p(double x)
Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.
|
| Modifier and Type | Method and Description |
|---|---|
double |
WilcoxonSignedRankTest.wilcoxonSignedRankTest(double[] x,
double[] y,
boolean exactPValue)
Returns the observed significance level, or
p-value, associated with a
Wilcoxon signed ranked statistic comparing mean for two related
samples or repeated measurements on a single sample.
|
| Modifier and Type | Method and Description |
|---|---|
ConfidenceInterval |
BinomialConfidenceInterval.createInterval(int numberOfTrials,
int numberOfSuccesses,
double confidenceLevel)
Create a confidence interval for the true probability of success
of an unknown binomial distribution with the given observed number
of trials, successes and confidence level.
|
| Modifier and Type | Method and Description |
|---|---|
static long |
CombinatoricsUtils.binomialCoefficient(int n,
int k)
Returns an exact representation of the Binomial
Coefficient, "
n choose k", the number of
k-element subsets that can be selected from an
n-element set. |
static long |
ArithmeticUtils.binomialCoefficient(int n,
int k)
Deprecated.
|
static double |
CombinatoricsUtils.binomialCoefficientDouble(int n,
int k)
Returns a
double representation of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set. |
static double |
ArithmeticUtils.binomialCoefficientDouble(int n,
int k)
Deprecated.
|
static double |
CombinatoricsUtils.binomialCoefficientLog(int n,
int k)
Returns the natural
log of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set. |
static double |
ArithmeticUtils.binomialCoefficientLog(int n,
int k)
Deprecated.
|
static void |
CombinatoricsUtils.checkBinomial(int n,
int k)
Check binomial preconditions.
|
static long |
CombinatoricsUtils.stirlingS2(int n,
int k)
Returns the
Stirling number of the second kind, "
S(n,k)", the number of
ways of partitioning an n-element set into k non-empty
subsets. |
static long |
ArithmeticUtils.stirlingS2(int n,
int k)
Deprecated.
|
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