double[] data
DSFactory factory
private Object writeReplace()
double halfSampleSpan
int nbPoints
double stepSize
double tMax
double tMin
double accuracy
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[] 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
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.int omegaCount
double[] omegaImaginaryClockwise
n
-th roots of unity, for negative values
of n
. In this array, the roots are stored in clockwise order.double[] omegaImaginaryCounterClockwise
n
-th roots of unity, for positive values
of n
. In this array, the roots are stored in counter-clockwise
order.double[] omegaReal
double[] cumulativeProbabilities
double[] probabilities
List<E extends Object> singletons
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 logMean
double mean
double denominatorDegreesOfFreedom
double numeratorDegreesOfFreedom
double numericalVariance
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 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 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 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 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 minY
y = x / scale
for the selection of the computation
method in GammaDistribution.density(double)
. For y <= minY
, the natural
calculation overflows.double scale
double shape
double shiftedShape
double beta
double mu
double beta
double mu
double c
double halfC
double mu
double mu
double s
double logShapePlusHalfLog2Pi
log(shape) + 0.5 * log(2*PI)
stored for faster computation.double scale
double shape
double mu
double omega
double logStandardDeviationPlusHalfLog2Pi
log(sd) + 0.5*log(2*pi)
stored for faster computation.double mean
double standardDeviation
double scale
double shape
double degreesOfFreedom
double factor
double a
double b
double c
double lower
double upper
double scale
double shape
int numberOfTrials
double probabilityOfSuccess
EnumeratedDistribution<T> innerDistribution
EnumeratedDistribution
instance (using the Integer
wrapper)
used to generate the pmf.double log1mProbabilityOfSuccess
log(1 - p)
where p is the probability of success.double logProbabilityOfSuccess
log(p)
where p is the probability of success.double probabilityOfSuccess
int numberOfSuccesses
double numericalVariance
int populationSize
int sampleSize
double log1mProbabilityOfSuccess
log(1-p)
, where p
is the probability of success,
stored for faster computation.double logProbabilityOfSuccess
log(p)
, where p
is the probability of success,
stored for faster computation.int numberOfSuccesses
double probabilityOfSuccess
double epsilon
int maxIterations
Gamma.regularizedGammaP(double, double, double, int)
or continued fraction approximation of
Gamma.regularizedGammaQ(double, double, double, int)
.double mean
NormalDistribution normal
int lower
int upper
double exponent
double nthHarmonic
int numberOfElements
double numericalMean
boolean numericalMeanIsCalculated
double numericalVariance
boolean numericalVarianceIsCalculated
String source
Object[] parts
Localizable specifier
Object[] parts
Localizable specifier
double weight
double x
double y
BigInteger denominator
BigInteger numerator
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()
double[][] jacobian
double phi
double[][] phiHessian
double r
double[][] rHessian
double theta
double[][] thetaHessian
Vector3D v
double x
double y
double z
private Object readResolve()
double x
double y
double tolerance
Vector2D[] vertices
double alpha
Vector2D vector
private Object readResolve()
double phi
double theta
Vector3D vector
private Object readResolve()
FieldElement<T>[][] data
double[][] data
FieldElement<T>[] data
Field<T> field
double[] data
int blockColumns
int blockRows
FieldElement<T>[][] blocks
int columns
int rows
int blockColumns
int blockRows
double[][] blocks
int columns
int rows
RealVector b
RealVector r
double rnorm
RealVector x
double[] data
int columns
OpenIntToDoubleHashMap entries
int rows
OpenIntToDoubleHashMap entries
double epsilon
int virtualSize
OpenIntToFieldHashMap<T extends FieldElement<T>> entries
Field<T> field
int virtualSize
int dimension
Number argument
Number max
double fHi
double fLo
double hi
double lo
MathArrays.OrderDirection direction
int index
Number previous
boolean strict
boolean boundIsAllowed
Number max
boolean boundIsAllowed
Number min
int index
double threshold
int column
int row
double threshold
double interpolatedTime
String name
int[] start
int[] start
int completeDimension
double[] primaryState
double[][] secondaryState
double time
double[] primaryDerivative
double[][] secondaryDerivative
boolean forward
ODEStateAndDerivative globalCurrentState
ODEStateAndDerivative globalPreviousState
EquationsMapper mapper
ODEStateAndDerivative softCurrentState
ODEStateAndDerivative softPreviousState
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[] arr
int count
int isaacA
int isaacB
int isaacC
int isaacI
int isaacJ
int isaacX
int[] mem
int[] rsl
Random delegate
int[] mt
int mti
RandomGenerator randomGenerator
RandomGenerator randomGenerator
JComponent container
JComponent container
BufferedImage clusterImage
JSpinner clusterSizeSpinner
org.hipparchus.samples.clustering.ImageClusteringExample.Display.ImagePainter painter
BufferedImage referenceImage
Raster referenceRaster
org.piccolo2d.PCanvas canvas
JComponent container
JComponent controlPanel
List<E extends Object> points
NavigableMap<K extends Object,V extends Object> freqTable
ResizableDoubleArray eDA
UnivariateStatistic geometricMeanImpl
UnivariateStatistic kurtosisImpl
UnivariateStatistic maxImpl
UnivariateStatistic meanImpl
UnivariateStatistic minImpl
Percentile percentileImpl
UnivariateStatistic skewnessImpl
UnivariateStatistic sumImpl
UnivariateStatistic sumOfSquaresImpl
UnivariateStatistic varianceImpl
int windowSize
VectorialCovariance covarianceImpl
StorelessMultivariateStatistic geoMeanImpl
int k
StorelessMultivariateStatistic maxImpl
StorelessMultivariateStatistic meanImpl
StorelessMultivariateStatistic minImpl
long n
StorelessMultivariateStatistic sumImpl
StorelessMultivariateStatistic sumLogImpl
StorelessMultivariateStatistic sumSqImpl
double max
double mean
double min
long n
double sum
double variance
boolean computeExtrema
boolean computeMoments
boolean computePercentiles
boolean computeSumOfLogs
boolean computeSumOfSquares
GeometricMean geoMeanImpl
Max maxImpl
Mean meanImpl
Min minImpl
long n
Variance populationVariance
RandomPercentile randomPercentile
SecondMoment secondMoment
Sum sumImpl
SumOfLogs sumOfLogsImpl
SumOfSquares sumOfSquaresImpl
Variance varianceImpl
boolean incSumOfLogs
Statistics based on (constructed from) external statistics cannot be incremented or cleared.
SumOfLogs sumOfLogs
boolean incMoment
Statistics based on (constructed from) external moments 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
double m2
boolean biasCorrected
SemiVariance.Direction varianceDirection
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
org.hipparchus.stat.descriptive.moment.ThirdMoment moment
Variance variance
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.SecondMoment moment
long n
double value
Percentile percentile
long n
double value
int[] cachedPivots
Percentile.EstimationType estimationType
Percentile.EstimationType
s such as CM
can be used.KthSelector kthSelector
NaNStrategy nanStrategy
NaNStrategy
double quantile
long countOfObservations
List<E extends Object> initialFive
PSquarePercentile.PSquareMarkers markers
double pValue
double quantile
PSquarePercentile(double)
ensures that passed in percentile is
divided by 100.org.hipparchus.stat.descriptive.rank.RandomPercentile.BufferMap bufferMap
org.hipparchus.stat.descriptive.rank.RandomPercentile.Buffer currentBuffer
double epsilon
int h
long n
RandomGenerator randomGenerator
int s
long n
double value
long n
double value
int n
double value
long n
double value
boolean isBiasCorrected
long n
double[] productsSums
double[] sums
StorelessUnivariateStatistic[] stats
int binCount
List<E extends Object> binStats
double delta
boolean loaded
double max
double min
RandomDataGenerator randomData
StreamingStatistics sampleStats
double[] upperBounds
boolean containsConstant
double[] globalFitInfo
boolean isSymmetricVCD
long nobs
double[] parameters
int rank
double[][] varCovData
boolean hasIntercept
long n
double sumX
double sumXX
double sumXY
double sumY
double sumYY
double xbar
double ybar
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
int mask
double missingEntries
int size
byte[] states
double[] values
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
int mask
FieldElement<T> missingEntries
int size
byte[] states
FieldElement<T>[] values
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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