private java.lang.Object writeReplace()
double[] data
int nbPoints
double stepSize
double halfSampleSpan
double tMin
double tMax
double value
java.util.Map<K,V> derivatives
double bandwidth
int robustnessIters
double accuracy
double[] coefficients
protected final java.lang.Object readResolve()
Complex.createComplex(double, double)
to
deserialize properly.double imaginary
double real
private java.lang.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.RandomDataImpl randomData
AbstractIntegerDistribution.random
instance variable instead.RandomGenerator random
RandomDataImpl randomData
AbstractRealDistribution.random
instance variable instead.RandomGenerator random
double solverAbsoluteAccuracy
double alpha
double beta
double z
double solverAbsoluteAccuracy
int numberOfTrials
double probabilityOfSuccess
double median
double scale
double solverAbsoluteAccuracy
GammaDistribution gamma
double solverAbsoluteAccuracy
double value
RandomGenerator random
java.util.List<E> singletons
double[] probabilities
double[] cumulativeProbabilities
EnumeratedDistribution<T> innerDistribution
EnumeratedDistribution
instance (using the Integer
wrapper)
used to generate the pmf.EnumeratedDistribution<T> innerDistribution
EnumeratedDistribution
(using the Double
wrapper)
used to generate the pmf.double mean
double logMean
double solverAbsoluteAccuracy
double numeratorDegreesOfFreedom
double denominatorDegreesOfFreedom
double solverAbsoluteAccuracy
double numericalVariance
boolean numericalVarianceIsCalculated
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 solverAbsoluteAccuracy
double probabilityOfSuccess
double mu
double beta
int numberOfSuccesses
int populationSize
int sampleSize
double numericalVariance
boolean numericalVarianceIsCalculated
int n
double mu
double beta
double mu
double c
double halfC
double mu
double s
double scale
double shape
double logShapePlusHalfLog2Pi
log(shape) + 0.5 * log(2*PI)
stored for faster computation.double solverAbsoluteAccuracy
double mu
double omega
double inverseAbsoluteAccuracy
double mean
double standardDeviation
double logStandardDeviationPlusHalfLog2Pi
log(sd) + 0.5*log(2*pi)
stored for faster computation.double solverAbsoluteAccuracy
double scale
double shape
double solverAbsoluteAccuracy
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
ExponentialDistribution exponential
PoissonDistribution.sample()
method.double mean
int maxIterations
Gamma.regularizedGammaP(double, double, double, int)
or continued fraction approximation of
Gamma.regularizedGammaQ(double, double, double, int)
.double epsilon
double degreesOfFreedom
double solverAbsoluteAccuracy
double factor
double a
double b
double c
double solverAbsoluteAccuracy
int lower
int upper
double lower
double upper
double shape
double scale
double solverAbsoluteAccuracy
double numericalMean
boolean numericalMeanIsCalculated
double numericalVariance
boolean numericalVarianceIsCalculated
int numberOfElements
double exponent
double numericalMean
boolean numericalMeanIsCalculated
double numericalVariance
boolean numericalVarianceIsCalculated
int dimension
ExceptionContext context
ExceptionContext context
java.lang.Number argument
ExceptionContext context
ExceptionContext context
ExceptionContext context
java.lang.Number max
java.lang.Integer[] wrong
java.lang.Integer[] expected
double lo
double hi
double fLo
double fHi
MathArrays.OrderDirection direction
boolean strict
int index
java.lang.Number previous
java.lang.Number max
boolean boundIsAllowed
java.lang.Number min
boolean boundIsAllowed
java.lang.Number lo
java.lang.Number hi
java.lang.String source
private void readObject(java.io.ObjectInputStream in) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
- This should never happen.java.lang.ClassNotFoundException
- This should never happen.private void writeObject(java.io.ObjectOutputStream out) throws java.io.IOException
java.io.IOException
- This should never happen.java.lang.Throwable throwable
java.util.List<E> msgPatterns
java.util.List<E> msgArguments
ExceptionContext.msgPatterns
.java.util.Map<K,V> context
double weight
double x
double y
java.util.List<E> observations
java.text.NumberFormat denominatorFormat
java.text.NumberFormat numeratorFormat
java.math.BigInteger numerator
java.math.BigInteger denominator
private java.lang.Object readResolve()
int denominator
int numerator
private java.lang.Object readResolve()
java.text.NumberFormat wholeFormat
java.text.NumberFormat wholeFormat
private java.lang.Object readResolve()
double x
private java.lang.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 java.lang.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 java.lang.Object readResolve()
double x
double y
Vector2D[] vertices
double tolerance
double alpha
Vector2D vector
private java.lang.Object readResolve()
double theta
double phi
Vector3D vector
private java.lang.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 index
double threshold
int row
int column
double threshold
int rows
int columns
OpenIntToDoubleHashMap entries
OpenIntToDoubleHashMap entries
int virtualSize
double epsilon
Field<T> field
OpenIntToFieldHashMap<T extends FieldElement<T>> entries
int virtualSize
Clusterable center
java.util.List<E> points
double[] point
private void readObject(java.io.ObjectInputStream in)
private java.lang.Object writeReplace()
java.util.concurrent.ConcurrentHashMap<K,V> neuronMap
java.util.concurrent.atomic.AtomicLong nextId
int featureSize
java.util.concurrent.ConcurrentHashMap<K,V> linkMap
private void readObject(java.io.ObjectInputStream in)
private java.lang.Object writeReplace()
long identifier
int size
java.util.concurrent.atomic.AtomicReference<V> features
private void readObject(java.io.ObjectInputStream in)
private java.lang.Object writeReplace()
Network network
int size
boolean wrap
long[] identifiers
NeuronString.network
instance).private void readObject(java.io.ObjectInputStream in)
private java.lang.Object writeReplace()
Network network
int numberOfRows
int numberOfColumns
boolean wrapRows
boolean wrapColumns
SquareNeighbourhood neighbourhood
long[][] identifiers
NeuronSquareMesh2D.network
instance).double initialTime
double finalTime
boolean forward
int index
java.util.List<E> steps
int firstIndex
int dimension
java.lang.String name
public abstract void readExternal(java.io.ObjectInput in) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
java.lang.ClassNotFoundException
public abstract void writeExternal(java.io.ObjectOutput out) throws java.io.IOException
java.io.IOException
public void readExternal(java.io.ObjectInput in) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
java.lang.ClassNotFoundException
public void writeExternal(java.io.ObjectOutput out) throws java.io.IOException
java.io.IOException
private java.lang.Object writeReplace()
private java.lang.Object writeReplace()
private void readObject(java.io.ObjectInputStream ois) throws java.lang.ClassNotFoundException, java.io.IOException
java.lang.ClassNotFoundException
- if a class in the stream cannot be foundjava.io.IOException
- if object cannot be read from the streamprivate void writeObject(java.io.ObjectOutputStream oos) throws java.io.IOException
java.io.IOException
- if object cannot be written to streamRelationship relationship
double value
private void readObject(java.io.ObjectInputStream ois) throws java.lang.ClassNotFoundException, java.io.IOException
java.lang.ClassNotFoundException
- if a class in the stream cannot be foundjava.io.IOException
- if object cannot be read from the streamprivate void writeObject(java.io.ObjectOutputStream oos) throws java.io.IOException
java.io.IOException
- if object cannot be written to streamdouble constantTerm
double point
double value
private java.lang.Object writeReplace()
private java.lang.Object writeReplace()
double weight
double x
double y
private void readObject(java.io.ObjectInputStream ois) throws java.lang.ClassNotFoundException, java.io.IOException
java.lang.ClassNotFoundException
- if a class in the stream cannot be foundjava.io.IOException
- if object cannot be read from the streamprivate void writeObject(java.io.ObjectOutputStream oos) throws java.io.IOException
java.io.IOException
- if object cannot be written to streamRelationship relationship
double value
private void readObject(java.io.ObjectInputStream ois) throws java.lang.ClassNotFoundException, java.io.IOException
java.lang.ClassNotFoundException
- if a class in the stream cannot be foundjava.io.IOException
- if object cannot be read from the streamprivate void writeObject(java.io.ObjectOutputStream oos) throws java.io.IOException
java.io.IOException
- if object cannot be written to streamdouble constantTerm
double point
double value
int index
int[] v
int[] iRm1
int[] iRm2
int[] i1
int[] i2
int[] i3
double nextGaussian
RandomDataGenerator randomData
java.util.List<E> binStats
SummaryStatistics sampleStats
double max
double min
double delta
int binCount
boolean loaded
double[] upperBounds
int[] rsl
int[] mem
int count
int isaacA
int isaacB
int isaacC
int[] arr
int isaacX
int isaacI
int isaacJ
int[] mt
int mti
RandomGenerator randomGenerator
RandomGenerator rand
RandomGenerator secRand
RandomDataGenerator delegate
java.util.TreeMap<K,V> freqTable
java.util.List<E> points
Clusterable<T> center
double[] point
int[] point
SummaryStatistics statisticsPrototype
SummaryStatistics statistics
int windowSize
ResizableDoubleArray eDA
UnivariateStatistic meanImpl
UnivariateStatistic geometricMeanImpl
UnivariateStatistic kurtosisImpl
UnivariateStatistic maxImpl
UnivariateStatistic minImpl
UnivariateStatistic percentileImpl
UnivariateStatistic skewnessImpl
UnivariateStatistic varianceImpl
UnivariateStatistic sumsqImpl
UnivariateStatistic sumImpl
int k
long n
StorelessUnivariateStatistic[] sumImpl
StorelessUnivariateStatistic[] sumSqImpl
StorelessUnivariateStatistic[] minImpl
StorelessUnivariateStatistic[] maxImpl
StorelessUnivariateStatistic[] sumLogImpl
StorelessUnivariateStatistic[] geoMeanImpl
StorelessUnivariateStatistic[] meanImpl
VectorialCovariance covarianceImpl
double mean
double variance
long n
double max
double min
double sum
long n
SecondMoment secondMoment
Sum sum
SumOfSquares sumsq
Min min
Max max
SumOfLogs sumLog
GeometricMean geoMean
Mean mean
Variance variance
StorelessUnivariateStatistic sumImpl
StorelessUnivariateStatistic sumsqImpl
StorelessUnivariateStatistic minImpl
StorelessUnivariateStatistic maxImpl
StorelessUnivariateStatistic sumLogImpl
StorelessUnivariateStatistic geoMeanImpl
StorelessUnivariateStatistic meanImpl
StorelessUnivariateStatistic varianceImpl
StorelessUnivariateStatistic sumOfLogs
FourthMoment moment
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
FirstMoment moment
boolean incMoment
Statistics based on (constructed from) external moments cannot be incremented or cleared.
double m2
boolean biasCorrected
SemiVariance.Direction varianceDirection
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.double[] sums
double[] productsSums
boolean isBiasCorrected
long n
Mean[] means
long n
double value
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
java.util.List<E> initialFive
double quantile
PSquarePercentile.PSquarePercentile(double)
ensures that passed in percentile is
divided by 100.PSquarePercentile.PSquareMarkers markers
double pValue
long countOfObservations
long n
double value
long n
double value
int n
double value
long n
double value
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
java.math.BigDecimal d
java.math.RoundingMode roundingMode
int scale
private java.lang.Object readResolve()
double value
double
value of this object.int iterations
PivotingStrategyInterface pivotingStrategy
PivotingStrategyInterface
used for pivotingprivate void readObject(java.io.ObjectInputStream stream) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
- if object cannot be readjava.lang.ClassNotFoundException
- 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(java.io.ObjectInputStream stream) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
- if object cannot be readjava.lang.ClassNotFoundException
- 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
RandomGenerator random
double contractionCriterion
double expansionFactor
internalArray.length * expansionFactor
if expansionMode
is set to MULTIPLICATIVE_MODE, or
internalArray.length + expansionFactor
if
expansionMode
is set to ADDITIVE_MODE.ResizableDoubleArray.ExpansionMode expansionMode
expansionFactor
is additive or multiplicative.double[] internalArray
int numElements
int startIndex
internalArray[startIndex],...,internalArray[startIndex + numElements - 1]
.NumberTransformer defaultTransformer
java.util.Map<K,V> map