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Packages that use NotPositiveException | |
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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.interpolation | Univariate real functions interpolation algorithms. |
org.apache.commons.math3.complex | Complex number type and implementations of complex transcendental 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.linear | Linear algebra support. |
org.apache.commons.math3.ml.clustering | Clustering algorithms. |
org.apache.commons.math3.optim.nonlinear.scalar.noderiv | This package provides optimization algorithms that do not require derivatives. |
org.apache.commons.math3.optimization.direct | This package provides optimization algorithms that don't require derivatives. |
org.apache.commons.math3.random | Random number and random data generators. |
org.apache.commons.math3.stat.clustering | All classes and sub-packages of this package are deprecated. |
org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction. |
org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library. |
Uses of NotPositiveException in org.apache.commons.math3.analysis.differentiation |
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Constructors in org.apache.commons.math3.analysis.differentiation that throw NotPositiveException | |
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FiniteDifferencesDifferentiator(int nbPoints,
double stepSize)
Build a differentiator with number of points and step size when independent variable is unbounded. |
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FiniteDifferencesDifferentiator(int nbPoints,
double stepSize,
double tLower,
double tUpper)
Build a differentiator with number of points and step size when independent variable is bounded. |
Uses of NotPositiveException in org.apache.commons.math3.analysis.interpolation |
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Constructors in org.apache.commons.math3.analysis.interpolation that throw NotPositiveException | |
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LoessInterpolator(double bandwidth,
int robustnessIters,
double accuracy)
Construct a new LoessInterpolator
with given bandwidth, number of robustness iterations and accuracy. |
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MicrosphereInterpolator(int elements,
int exponent)
Create a microsphere interpolator. |
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SmoothingPolynomialBicubicSplineInterpolator(int degree)
|
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SmoothingPolynomialBicubicSplineInterpolator(int xDegree,
int yDegree)
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Uses of NotPositiveException in org.apache.commons.math3.complex |
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Methods in org.apache.commons.math3.complex that throw NotPositiveException | |
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List<Complex> |
Complex.nthRoot(int n)
Computes the n-th roots of this complex number. |
Uses of NotPositiveException in org.apache.commons.math3.distribution |
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Constructors in org.apache.commons.math3.distribution that throw NotPositiveException | |
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EnumeratedDistribution(List<Pair<T,Double>> pmf)
Create an enumerated distribution using the given probability mass function enumeration. |
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EnumeratedDistribution(RandomGenerator rng,
List<Pair<T,Double>> pmf)
Create an enumerated distribution using the given random number generator and probability mass function enumeration. |
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EnumeratedIntegerDistribution(int[] singletons,
double[] probabilities)
Create a discrete distribution using the given probability mass function definition. |
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EnumeratedIntegerDistribution(RandomGenerator rng,
int[] singletons,
double[] probabilities)
Create a discrete distribution using the given random number generator and probability mass function definition. |
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EnumeratedRealDistribution(double[] singletons,
double[] probabilities)
Create a discrete distribution using the given probability mass function enumeration. |
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EnumeratedRealDistribution(RandomGenerator rng,
double[] singletons,
double[] probabilities)
Create a discrete distribution using the given random number generator and probability mass function enumeration. |
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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. |
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HypergeometricDistribution(RandomGenerator rng,
int populationSize,
int numberOfSuccesses,
int sampleSize)
Creates a new hypergeometric distribution. |
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MixtureMultivariateNormalDistribution(RandomGenerator rng,
List<Pair<Double,MultivariateNormalDistribution>> components)
Creates a mixture model from a list of distributions and their associated weights. |
Uses of NotPositiveException in org.apache.commons.math3.genetics |
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Methods in org.apache.commons.math3.genetics that throw NotPositiveException | |
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void |
ListPopulation.setPopulationLimit(int populationLimit)
Sets the maximal population size. |
Constructors in org.apache.commons.math3.genetics that throw NotPositiveException | |
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ElitisticListPopulation(int populationLimit,
double elitismRate)
Creates a new ElitisticListPopulation instance and initializes its inner chromosome list. |
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ElitisticListPopulation(List<Chromosome> chromosomes,
int populationLimit,
double elitismRate)
Creates a new ElitisticListPopulation instance. |
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ListPopulation(int populationLimit)
Creates a new ListPopulation instance and initializes its inner chromosome list. |
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ListPopulation(List<Chromosome> chromosomes,
int populationLimit)
Creates a new ListPopulation instance. |
Uses of NotPositiveException in org.apache.commons.math3.linear |
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Methods in org.apache.commons.math3.linear that throw NotPositiveException | |
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abstract RealVector |
RealVector.getSubVector(int index,
int n)
Get a subvector from consecutive elements. |
FieldVector<T> |
ArrayFieldVector.getSubVector(int index,
int n)
Get a subvector from consecutive elements. |
FieldVector<T> |
FieldVector.getSubVector(int index,
int n)
Get a subvector from consecutive elements. |
FieldVector<T> |
SparseFieldVector.getSubVector(int index,
int n)
Deprecated. Get a subvector from consecutive elements. |
RealVector |
ArrayRealVector.getSubVector(int index,
int n)
Get a subvector from consecutive elements. |
OpenMapRealVector |
OpenMapRealVector.getSubVector(int index,
int n)
Deprecated. Get a subvector from consecutive elements. |
FieldMatrix<T> |
FieldMatrix.power(int p)
Returns the result multiplying this with itself p times. |
RealMatrix |
AbstractRealMatrix.power(int p)
Returns the result of multiplying this with itself p
times. |
RealMatrix |
RealMatrix.power(int p)
Returns the result of multiplying this with itself p
times. |
FieldMatrix<T> |
AbstractFieldMatrix.power(int p)
Returns the result multiplying this with itself p times. |
Uses of NotPositiveException in org.apache.commons.math3.ml.clustering |
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Constructors in org.apache.commons.math3.ml.clustering that throw NotPositiveException | |
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DBSCANClusterer(double eps,
int minPts)
Creates a new instance of a DBSCANClusterer. |
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DBSCANClusterer(double eps,
int minPts,
DistanceMeasure measure)
Creates a new instance of a DBSCANClusterer. |
Uses of NotPositiveException in org.apache.commons.math3.optim.nonlinear.scalar.noderiv |
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Constructors in org.apache.commons.math3.optim.nonlinear.scalar.noderiv that throw NotPositiveException | |
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CMAESOptimizer.Sigma(double[] s)
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Uses of NotPositiveException in org.apache.commons.math3.optimization.direct |
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Constructors in org.apache.commons.math3.optimization.direct that throw NotPositiveException | |
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CMAESOptimizer.Sigma(double[] s)
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Uses of NotPositiveException in org.apache.commons.math3.random |
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Methods in org.apache.commons.math3.random that throw NotPositiveException | |
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int |
RandomDataImpl.nextHypergeometric(int populationSize,
int numberOfSuccesses,
int sampleSize)
Deprecated. Generates a random value from the Hypergeometric Distribution . |
int |
RandomDataGenerator.nextHypergeometric(int populationSize,
int numberOfSuccesses,
int sampleSize)
Generates a random value from the Hypergeometric Distribution . |
Uses of NotPositiveException in org.apache.commons.math3.stat.clustering |
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Constructors in org.apache.commons.math3.stat.clustering that throw NotPositiveException | |
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DBSCANClusterer(double eps,
int minPts)
Deprecated. Creates a new instance of a DBSCANClusterer. |
Uses of NotPositiveException in org.apache.commons.math3.stat.inference |
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Methods in org.apache.commons.math3.stat.inference that throw NotPositiveException | |
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double |
ChiSquareTest.chiSquare(double[] expected,
long[] observed)
Computes the Chi-Square statistic comparing observed and expected
frequency counts. |
static double |
TestUtils.chiSquare(double[] expected,
long[] observed)
|
double |
ChiSquareTest.chiSquare(long[][] counts)
Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
static double |
TestUtils.chiSquare(long[][] counts)
|
double |
ChiSquareTest.chiSquareDataSetsComparison(long[] observed1,
long[] observed2)
Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2 . |
static double |
TestUtils.chiSquareDataSetsComparison(long[] observed1,
long[] observed2)
|
double |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed
frequency counts to those in the expected array. |
static double |
TestUtils.chiSquareTest(double[] expected,
long[] observed)
|
boolean |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha . |
static boolean |
TestUtils.chiSquareTest(double[] expected,
long[] observed,
double alpha)
|
double |
ChiSquareTest.chiSquareTest(long[][] counts)
Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
static double |
TestUtils.chiSquareTest(long[][] counts)
|
boolean |
ChiSquareTest.chiSquareTest(long[][] counts,
double alpha)
Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha . |
static boolean |
TestUtils.chiSquareTest(long[][] counts,
double alpha)
|
double |
ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in observed1 and
observed2 . |
static double |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
|
boolean |
ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
Performs a Chi-Square two sample test comparing two binned data sets. |
static boolean |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
|
static double |
TestUtils.g(double[] expected,
long[] observed)
|
double |
GTest.g(double[] expected,
long[] observed)
Computes the G statistic for Goodness of Fit comparing observed and expected
frequency counts. |
static double |
TestUtils.gDataSetsComparison(long[] observed1,
long[] observed2)
|
double |
GTest.gDataSetsComparison(long[] observed1,
long[] observed2)
Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2 . |
static double |
TestUtils.gTest(double[] expected,
long[] observed)
|
double |
GTest.gTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing the observed frequency counts to those in the expected array. |
static boolean |
TestUtils.gTest(double[] expected,
long[] observed,
double alpha)
|
boolean |
GTest.gTest(double[] expected,
long[] observed,
double alpha)
Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha . |
static double |
TestUtils.gTestDataSetsComparison(long[] observed1,
long[] observed2)
|
double |
GTest.gTestDataSetsComparison(long[] observed1,
long[] observed2)
Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts in observed1 and
observed2 . |
static boolean |
TestUtils.gTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
|
boolean |
GTest.gTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets. |
static double |
TestUtils.gTestIntrinsic(double[] expected,
long[] observed)
|
double |
GTest.gTestIntrinsic(double[] expected,
long[] observed)
Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H. 2009. |
static double |
TestUtils.rootLogLikelihoodRatio(long k11,
long k12,
long k21,
long k22)
|
Uses of NotPositiveException in org.apache.commons.math3.util |
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Methods in org.apache.commons.math3.util that throw NotPositiveException | |
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static long |
ArithmeticUtils.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 double |
ArithmeticUtils.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.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 void |
MathArrays.checkNonNegative(long[] in)
Check that all entries of the input array are >= 0. |
static void |
MathArrays.checkNonNegative(long[][] in)
Check all entries of the input array are >= 0. |
static long |
ArithmeticUtils.factorial(int n)
Returns n!. |
static double |
ArithmeticUtils.factorialDouble(int n)
Compute n! |
static double |
ArithmeticUtils.factorialLog(int n)
Compute the natural logarithm of the factorial of n . |
static BigInteger |
ArithmeticUtils.pow(BigInteger k,
BigInteger e)
Raise a BigInteger to a BigInteger power. |
static BigInteger |
ArithmeticUtils.pow(BigInteger k,
int e)
Raise a BigInteger to an int power. |
static BigInteger |
ArithmeticUtils.pow(BigInteger k,
long e)
Raise a BigInteger to a long power. |
static int |
ArithmeticUtils.pow(int k,
int e)
Raise an int to an int power. |
static int |
ArithmeticUtils.pow(int k,
long e)
Raise an int to a long power. |
static long |
ArithmeticUtils.pow(long k,
int e)
Raise a long to an int power. |
static long |
ArithmeticUtils.pow(long k,
long e)
Raise a long to a long power. |
static long |
ArithmeticUtils.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. |
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