DSFactory factory
double[] data
private Object writeReplace()
int nbPoints
double stepSize
double halfSampleSpan
double tMin
double tMax
double[] grid
int n
AtomicInteger cache
double bandwidth
A sensible value is usually 0.25 to 0.5.
int robustnessIters
A sensible value is usually 0 (just the initial fit without any robustness iterations) to 4.
double accuracy
double[] coefficients
Clusterable center
double[] point
protected final Object readResolve()
Complex.createComplex(double, double)
to
deserialize properly.double imaginary
double real
private Object readResolve()
double q0
double q1
double q2
double q3
int omegaCount
double[] omegaReal
double[] omegaImaginaryCounterClockwise
n
-th roots of unity, for positive values
of n
. In this array, the roots are stored in counter-clockwise
order.double[] omegaImaginaryClockwise
n
-th roots of unity, for negative values
of n
. In this array, the roots are stored in clockwise order.boolean isCounterClockWise
true
if RootsOfUnity.computeRoots(int)
was called with a positive
value of its argument n
. In this case, counter-clockwise ordering
of the roots of unity should be used.List<E> singletons
double[] probabilities
double solverAbsoluteAccuracy
double alpha
double beta
double z
double median
double scale
GammaDistribution gamma
double value
EnumeratedDistribution<T> innerDistribution
EnumeratedDistribution
(using the Double
wrapper)
used to generate the pmf.double mean
double logMean
double numeratorDegreesOfFreedom
double denominatorDegreesOfFreedom
double numericalVariance
double shape
double scale
double shiftedShape
double densityPrefactor1
shape / scale * sqrt(e / (2 * pi * (shape + g + 0.5))) / L(shape)
,
where L(shape)
is the Lanczos approximation returned by
Gamma.lanczos(double)
. This prefactor is used in
GammaDistribution.density(double)
, when no overflow occurs with the natural
calculation.double logDensityPrefactor1
log(shape / scale * sqrt(e / (2 * pi * (shape + g + 0.5))) / L(shape))
,
where L(shape)
is the Lanczos approximation returned by
Gamma.lanczos(double)
. This prefactor is used in
GammaDistribution.logDensity(double)
, when no overflow occurs with the natural
calculation.double densityPrefactor2
shape * sqrt(e / (2 * pi * (shape + g + 0.5))) / L(shape)
,
where L(shape)
is the Lanczos approximation returned by
Gamma.lanczos(double)
. This prefactor is used in
GammaDistribution.density(double)
, when overflow occurs with the natural
calculation.double logDensityPrefactor2
log(shape * sqrt(e / (2 * pi * (shape + g + 0.5))) / L(shape))
,
where L(shape)
is the Lanczos approximation returned by
Gamma.lanczos(double)
. This prefactor is used in
GammaDistribution.logDensity(double)
, when overflow occurs with the natural
calculation.double minY
y = x / scale
for the selection of the computation
method in GammaDistribution.density(double)
. For y <= minY
, the natural
calculation overflows.double maxLogY
log(y)
(y = x / scale
) for the selection
of the computation method in GammaDistribution.density(double)
. For
log(y) >= maxLogY
, the natural calculation overflows.double mu
double beta
double mu
double beta
double mu
double c
double halfC
double mu
double s
double location
double shape
double logShapePlusHalfLog2Pi
log(shape) + 0.5 * log(2*PI)
stored for faster computation.double mu
double omega
double mean
double standardDeviation
double logStandardDeviationPlusHalfLog2Pi
log(sd) + 0.5*log(2*pi)
stored for faster computation.double scale
double shape
double degreesOfFreedom
double factor
double a
double b
double c
double lower
double upper
double shape
double scale
int numberOfTrials
double probabilityOfSuccess
EnumeratedDistribution<T> innerDistribution
EnumeratedDistribution
instance (using the Integer
wrapper)
used to generate the pmf.double probabilityOfSuccess
double logProbabilityOfSuccess
log(p)
where p is the probability of success.double log1mProbabilityOfSuccess
log(1 - p)
where p is the probability of success.int numberOfSuccesses
int populationSize
int sampleSize
double numericalVariance
int numberOfSuccesses
double probabilityOfSuccess
double logProbabilityOfSuccess
log(p)
, where p
is the probability of success,
stored for faster computation.double log1mProbabilityOfSuccess
log(1-p)
, where p
is the probability of success,
stored for faster computation.NormalDistribution normal
double mean
int maxIterations
Gamma.regularizedGammaP(double, double, double, int)
or continued fraction approximation of
Gamma.regularizedGammaQ(double, double, double, int)
.double epsilon
int lower
int upper
int numberOfElements
double exponent
double nthHarmonic
double numericalMean
boolean numericalMeanIsCalculated
double numericalVariance
boolean numericalVarianceIsCalculated
String source
Localizable specifier
Object[] parts
Localizable specifier
Object[] parts
double weight
double x
double y
BigInteger numerator
BigInteger denominator
private Object readResolve()
int denominator
int numerator
private Object readResolve()
NumberFormat wholeFormat
NumberFormat wholeFormat
private Object readResolve()
double x
private Object readResolve()
RealFieldElement<T> q0
RealFieldElement<T> q1
RealFieldElement<T> q2
RealFieldElement<T> q3
RealFieldElement<T> x
RealFieldElement<T> y
RealFieldElement<T> z
double q0
double q1
double q2
double q3
private Object writeReplace()
Vector3D v
double r
double theta
double phi
double[][] jacobian
double[][] rHessian
double[][] thetaHessian
double[][] phiHessian
double x
double y
double z
private Object readResolve()
double x
double y
Vector2D[] vertices
double tolerance
double alpha
Vector2D vector
private Object readResolve()
double theta
double phi
Vector3D vector
private Object readResolve()
FieldElement<T>[][] data
double[][] data
FieldElement<T>[] data
Field<T> field
double[] data
FieldElement<T>[][] blocks
int rows
int columns
int blockRows
int blockColumns
double[][] blocks
int rows
int columns
int blockRows
int blockColumns
RealVector b
RealVector r
double rnorm
RealVector x
double[] data
int rows
int columns
OpenIntToDoubleHashMap entries
OpenIntToDoubleHashMap entries
int virtualSize
double epsilon
Field<T> field
OpenIntToFieldHashMap<T extends FieldElement<T>> entries
int virtualSize
int dimension
Number argument
Number max
double lo
double hi
double fLo
double fHi
MathArrays.OrderDirection direction
boolean strict
int index
Number previous
Number max
boolean boundIsAllowed
Number min
boolean boundIsAllowed
int index
double threshold
int row
int column
double threshold
double interpolatedTime
String name
int[] start
int[] start
double time
double[] primaryState
double[][] secondaryState
int completeDimension
double[] primaryDerivative
double[][] secondaryDerivative
ODEStateAndDerivative globalPreviousState
ODEStateAndDerivative globalCurrentState
ODEStateAndDerivative softPreviousState
ODEStateAndDerivative softCurrentState
boolean forward
EquationsMapper mapper
private Object writeReplace()
private Object writeReplace()
private void readObject(ObjectInputStream ois) throws ClassNotFoundException, IOException
ClassNotFoundException
- if a class in the stream cannot be foundIOException
- if object cannot be read from the streamprivate void writeObject(ObjectOutputStream oos) throws IOException
IOException
- if object cannot be written to streamRelationship relationship
double value
private void readObject(ObjectInputStream ois) throws ClassNotFoundException, IOException
ClassNotFoundException
- if a class in the stream cannot be foundIOException
- if object cannot be read from the streamprivate void writeObject(ObjectOutputStream oos) throws IOException
IOException
- if object cannot be written to streamdouble constantTerm
double point
double value
int index
int[] v
int[] rsl
int[] mem
int count
int isaacA
int isaacB
int isaacC
int[] arr
int isaacX
int isaacI
int isaacJ
Random delegate
int[] mt
int mti
RandomGenerator randomGenerator
RandomGenerator randomGenerator
JComponent container
JComponent container
BufferedImage referenceImage
BufferedImage clusterImage
Raster referenceRaster
org.hipparchus.samples.clustering.ImageClusteringExample.Display.ImagePainter painter
JSpinner clusterSizeSpinner
List<E> points
org.piccolo2d.PCanvas canvas
JComponent container
JComponent controlPanel
NavigableMap<K,V> freqTable
UnivariateStatistic maxImpl
UnivariateStatistic minImpl
UnivariateStatistic sumImpl
UnivariateStatistic sumOfSquaresImpl
UnivariateStatistic meanImpl
UnivariateStatistic varianceImpl
UnivariateStatistic geometricMeanImpl
UnivariateStatistic kurtosisImpl
UnivariateStatistic skewnessImpl
Percentile percentileImpl
int windowSize
ResizableDoubleArray eDA
int k
StorelessMultivariateStatistic sumImpl
StorelessMultivariateStatistic sumSqImpl
StorelessMultivariateStatistic minImpl
StorelessMultivariateStatistic maxImpl
StorelessMultivariateStatistic sumLogImpl
StorelessMultivariateStatistic geoMeanImpl
StorelessMultivariateStatistic meanImpl
VectorialCovariance covarianceImpl
long n
double mean
double variance
long n
double max
double min
double sum
long n
SecondMoment secondMoment
Min minImpl
Max maxImpl
Sum sumImpl
SumOfSquares sumOfSquaresImpl
SumOfLogs sumOfLogsImpl
Mean meanImpl
Variance varianceImpl
GeometricMean geoMeanImpl
Variance populationVariance
RandomPercentile randomPercentile
boolean computeMoments
boolean computeSumOfSquares
boolean computeSumOfLogs
boolean computePercentiles
boolean computeExtrema
SumOfLogs sumOfLogs
boolean incSumOfLogs
Statistics based on (constructed from) external statistics cannot be incremented or cleared.
org.hipparchus.stat.descriptive.moment.FourthMoment moment
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
org.hipparchus.stat.descriptive.moment.FirstMoment moment
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
double m2
boolean biasCorrected
SemiVariance.Direction varianceDirection
org.hipparchus.stat.descriptive.moment.ThirdMoment moment
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
Variance variance
SecondMoment moment
boolean incMoment
Variance.increment(double)
should increment
the internal second moment. When a Variance is constructed with an
external SecondMoment as a constructor parameter, this property is
set to false and increments must be applied to the second moment
directly.boolean isBiasCorrected
Variance
for details on the formula.long n
double value
Percentile percentile
long n
double value
KthSelector kthSelector
Percentile.EstimationType estimationType
Percentile.EstimationType
s such as CM
can be used.NaNStrategy nanStrategy
NaNStrategy
double quantile
int[] cachedPivots
List<E> initialFive
double quantile
PSquarePercentile.PSquarePercentile(double)
ensures that passed in percentile is
divided by 100.PSquarePercentile.PSquareMarkers markers
double pValue
long countOfObservations
int s
int h
org.hipparchus.stat.descriptive.rank.RandomPercentile.BufferMap bufferMap
double epsilon
RandomGenerator randomGenerator
long n
org.hipparchus.stat.descriptive.rank.RandomPercentile.Buffer currentBuffer
long n
double value
long n
double value
int n
double value
long n
double value
double[] sums
double[] productsSums
boolean isBiasCorrected
long n
StorelessUnivariateStatistic[] stats
RandomDataGenerator randomData
List<E> binStats
StreamingStatistics sampleStats
double max
double min
double delta
int binCount
boolean loaded
double[] upperBounds
double[] parameters
double[][] varCovData
boolean isSymmetricVCD
int rank
long nobs
boolean containsConstant
double[] globalFitInfo
double sumX
double sumXX
double sumY
double sumYY
double sumXY
long n
double xbar
double ybar
boolean hasIntercept
DctNormalization normalization
DftNormalization normalization
DstNormalization normalization
BigDecimal d
RoundingMode roundingMode
int scale
private Object readResolve()
double value
double
value of this object.private Object readResolve()
int iterations
PivotingStrategy pivotingStrategy
PivotingStrategy
used for pivoting.private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException
IOException
- if object cannot be readClassNotFoundException
- if the class corresponding
to the serialized object cannot be foundint[] keys
double[] values
byte[] states
double missingEntries
int size
int mask
private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException
IOException
- if object cannot be readClassNotFoundException
- if the class corresponding
to the serialized object cannot be foundField<T> field
int[] keys
FieldElement<T>[] values
byte[] states
FieldElement<T> missingEntries
int size
int mask
double contractionCriterion
double expansionFactor
internalArray.length * expansionFactor
if expansionMode
is set to MULTIPLICATIVE, or
internalArray.length + expansionFactor
if
expansionMode
is set to ADDITIVE.ResizableDoubleArray.ExpansionMode expansionMode
expansionFactor
is additive or multiplicative.double[] internalArray
int numElements
int startIndex
internalArray[startIndex],...,internalArray[startIndex + numElements - 1]
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