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RandomGenerator
interface.StorelessUnivariateStatistic
interface.UnivariateStatistic
interface.m
.
m
.
data
.
double[]
arrays.
double[]
arrays.
double[]
arrays.
double[]
arrays.
BigMatrix
using a BigDecimal[][] array to store entries
and
LU decompostion to support linear system
solution and inverse.data
as the underlying
data array.
data
as the underlying
data array.
data
as the underlying data array.
v
as the
data for the unique column of the v.length x 1
matrix
created.
n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
double
representation of the Binomial
Coefficient, "n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
log
of the Binomial
Coefficient, "n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
BinomialDistribution
. lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b],
this means that a
and b
bracket a root of f.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b],
this means that a
and b
bracket a root of f.
CauchyDistribution
.observed
and expected
frequency counts.
counts
array, viewed as a two-way table.
observed
and expected
frequency counts.
observed1
and observed2
.
ChiSquaredDistribution
observed
frequency counts to those in the expected
array.
alpha
.
counts
array, viewed as a two-way table.
alpha
.
observed
frequency counts to those in the expected
array.
alpha
.
observed1
and
observed2
.
UnknownDistributionChiSquareTest
interface.AbstractRandomGenerator.nextGaussian()
.
valuesFileURL
after use in REPLAY_MODE.
Comparable
arguments.
Complex
-valued functions.valuesFileURL
, using the default number of bins.
valuesFileURL
and binCount
bins.
direct search method
has converged.ConvergenceException.ConvergenceException(String, Object[], Throwable)
ConvergenceException.ConvergenceException(String, Object[])
RandomVectorGenerator
that generates vectors with with
correlated components.MathException
with specified
formatted detail message.
MathException
with specified
nested Throwable
root cause.
Random
using the supplied
RandomGenerator
.
dimension x dimension
identity matrix.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
dimension x dimension
identity matrix.
RealMatrix
whose entries are the the values in the
the input array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
x
).
x
).
x
).
x
).
DescriptiveStatistics
UnivariateRealFunction
representing a differentiable univariate real function.i initial elements of the array.
- DiscreteDistribution - Interface in org.apache.commons.math.distribution
- Base interface for discrete distributions.
- Distribution - Interface in org.apache.commons.math.distribution
- Base interface for probability distributions.
- distribution -
Variable in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
- Distribution used to compute inference statistics.
- distribution -
Variable in class org.apache.commons.math.stat.inference.TTestImpl
- Distribution used to compute inference statistics.
- distribution -
Variable in class org.apache.commons.math.stat.regression.SimpleRegression
- the distribution used to compute inference statistics.
- DistributionFactory - Class in org.apache.commons.math.distribution
- Deprecated. pluggability of distribution instances is now provided through
constructors and setters.
- DistributionFactory() -
Constructor for class org.apache.commons.math.distribution.DistributionFactory
- Deprecated. Default constructor.
- DistributionFactoryImpl - Class in org.apache.commons.math.distribution
- Deprecated. pluggability of distribution instances is now provided through
constructors and setters.
- DistributionFactoryImpl() -
Constructor for class org.apache.commons.math.distribution.DistributionFactoryImpl
- Deprecated. Default constructor.
- divide(Complex) -
Method in class org.apache.commons.math.complex.Complex
- Return the quotient of this complex number and the given complex number.
- divide(Fraction) -
Method in class org.apache.commons.math.fraction.Fraction
- Divide the value of this fraction by another.
- DividedDifferenceInterpolator - Class in org.apache.commons.math.analysis
- Implements the
Divided Difference Algorithm for interpolation of real univariate
functions.
- DividedDifferenceInterpolator() -
Constructor for class org.apache.commons.math.analysis.DividedDifferenceInterpolator
-
- doCopy() -
Method in class org.apache.commons.math.ode.AbstractStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.ClassicalRungeKuttaStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.DormandPrince54StepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.DormandPrince853StepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.DummyStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.EulerStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.GillStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.GraggBulirschStoerStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.HighamHall54StepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.MidpointStepInterpolator
- Really copy the finalized instance.
- doCopy() -
Method in class org.apache.commons.math.ode.ThreeEighthesStepInterpolator
- Really copy the finalized instance.
- doFinalize() -
Method in class org.apache.commons.math.ode.AbstractStepInterpolator
- Really finalize the step.
- doFinalize() -
Method in class org.apache.commons.math.ode.DormandPrince853StepInterpolator
- Really finalize the step.
- DormandPrince54Integrator - Class in org.apache.commons.math.ode
- This class implements the 5(4) Dormand-Prince integrator for Ordinary
Differential Equations.
- DormandPrince54Integrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.DormandPrince54Integrator
- Simple constructor.
- DormandPrince54Integrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.DormandPrince54Integrator
- Simple constructor.
- DormandPrince54StepInterpolator - Class in org.apache.commons.math.ode
- This class represents an interpolator over the last step during an
ODE integration for the 5(4) Dormand-Prince integrator.
- DormandPrince54StepInterpolator() -
Constructor for class org.apache.commons.math.ode.DormandPrince54StepInterpolator
- Simple constructor.
- DormandPrince54StepInterpolator(DormandPrince54StepInterpolator) -
Constructor for class org.apache.commons.math.ode.DormandPrince54StepInterpolator
- Copy constructor.
- DormandPrince853Integrator - Class in org.apache.commons.math.ode
- This class implements the 8(5,3) Dormand-Prince integrator for Ordinary
Differential Equations.
- DormandPrince853Integrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.DormandPrince853Integrator
- Simple constructor.
- DormandPrince853Integrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.DormandPrince853Integrator
- Simple constructor.
- DormandPrince853StepInterpolator - Class in org.apache.commons.math.ode
- This class represents an interpolator over the last step during an
ODE integration for the 8(5,3) Dormand-Prince integrator.
- DormandPrince853StepInterpolator() -
Constructor for class org.apache.commons.math.ode.DormandPrince853StepInterpolator
- Simple constructor.
- DormandPrince853StepInterpolator(DormandPrince853StepInterpolator) -
Constructor for class org.apache.commons.math.ode.DormandPrince853StepInterpolator
- Copy constructor.
- dotProduct(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the dot-product of two vectors.
- DoubleArray - Interface in org.apache.commons.math.util
- Provides a standard interface for double arrays.
- doubleValue() -
Method in class org.apache.commons.math.fraction.Fraction
- Gets the fraction as a double.
- DummyStepHandler - Class in org.apache.commons.math.ode
- This class is a step handler that do nothing.
- DummyStepHandler() -
Constructor for class org.apache.commons.math.ode.DummyStepHandler
- Private constructor.
- DummyStepInterpolator - Class in org.apache.commons.math.ode
- This class is a step interpolator that does nothing.
- DummyStepInterpolator() -
Constructor for class org.apache.commons.math.ode.DummyStepInterpolator
- Simple constructor.
- DummyStepInterpolator(double[], boolean) -
Constructor for class org.apache.commons.math.ode.DummyStepInterpolator
- Simple constructor.
- DummyStepInterpolator(DummyStepInterpolator) -
Constructor for class org.apache.commons.math.ode.DummyStepInterpolator
- Copy constructor.
- DuplicateSampleAbscissaException - Exception in org.apache.commons.math
- Exeption thrown when a sample contains several entries at the same abscissa.
- DuplicateSampleAbscissaException(double, int, int) -
Constructor for exception org.apache.commons.math.DuplicateSampleAbscissaException
- Construct an exception indicating the duplicate abscissa.
EmpiricalDistribution
interface.DataAdapter
for data provided as array of doubles.sampleStats
and
beanStats
abstracting the source of data.DataAdapter
objects.DataAdapter
for data provided through some input streamobject
is a
BigMatrixImpl
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is a
RealMatrixImpl
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is an
AbstractStorelessUnivariateStatistic
returning the same
values as this for getResult()
and getN()
object
is a SummaryStatistics
instance and all statistics have the same values as this.
object
is a
StatisticalSummaryValues
instance and all statistics have
the same values as this.
object
is a SummaryStatistics
instance and all statistics have the same values as this.
equals
AbstractStorelessUnivariateStatistic.clear()
, then invokes
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over the the input array, and then uses
AbstractStorelessUnivariateStatistic.getResult()
to compute the return value.
AbstractStorelessUnivariateStatistic.clear()
, then invokes
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over the specified portion of the input
array, and then uses AbstractStorelessUnivariateStatistic.getResult()
to compute the return value.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
p
th percentile of the values
in the values
array.
quantile
th percentile of the
designated values in the values
array.
p
th percentile of the values
in the values
array, starting with the element in (0-based)
position begin
in the array and including length
values.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
expansionFactor
is additive or multiplicative.
ExponentialDistribution
.FDistribution
.length
with values generated
using getNext() repeatedly.
Complex
object to produce a string.
Fraction
object to produce a string.
Fraction
object to produce a string.
FunctionEvaluationException.FunctionEvaluationException(double, String, Object[])
FunctionEvaluationException.FunctionEvaluationException(double, String, Object[], Throwable)
GammaDistribution
.Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
SummaryStatistics
containing statistics describing the values in each of the bins.
SummaryStatistics
instances containing
statistics describing the values in each of the bins.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array
of double values.
col
as an array
of double values.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a PDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
DoubleArray
.
ResizableArray
.
expansionMode
determines whether the internal storage
array grows additively (ADDITIVE_MODE) or multiplicatively
(MULTIPLICATIVE_MODE) when it is expanded.
MultivariateSummaryStatistics.addValue(double[])
MatrixUtils.createBigIdentityMatrix(int)
MatrixUtils.createRealIdentityMatrix(int)
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
p
, used to
bracket a CDF root.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
minimize
.
valuesFileURL
.
theoretical value
according to the parameter.
Fraction
instance with the 2 parts
of a fraction Y/Z.
BigDecimal.ROUND_HALF_UP
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array
of double values.
row
as an array
of double values.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
StatisticalSummary
describing this distribution.
StatisticalSummary
describing this distribution.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
StatisticalSummaryValues
instance reporting current
statistics.
MultivariateSummaryStatistics.addValue(double[])
valuesFileURL
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the variance of the available values.
- getVariance() -
Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
- Returns the variance of the available values.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
- Returns the variance of the values that have been added.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the currently configured variance implementation.
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
- Returns the currently configured variance implementation
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
- getWeight() -
Method in class org.apache.commons.math.estimation.WeightedMeasurement
- Get the weight of the measurement in the least squares problem
- getWholeFormat() -
Method in class org.apache.commons.math.fraction.ProperFractionFormat
- Access the whole format.
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
- Access the window size.
- getX() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the abscissa of the vector.
- getY() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the ordinate of the vector.
- getZ() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the height of the vector.
- GillIntegrator - Class in org.apache.commons.math.ode
- This class implements the Gill fourth order Runge-Kutta
integrator for Ordinary Differential Equations .
- GillIntegrator(double) -
Constructor for class org.apache.commons.math.ode.GillIntegrator
- Simple constructor.
- GillStepInterpolator - Class in org.apache.commons.math.ode
- This class implements a step interpolator for the Gill fourth
order Runge-Kutta integrator.
- GillStepInterpolator() -
Constructor for class org.apache.commons.math.ode.GillStepInterpolator
- Simple constructor.
- GillStepInterpolator(GillStepInterpolator) -
Constructor for class org.apache.commons.math.ode.GillStepInterpolator
- Copy constructor.
- GraggBulirschStoerIntegrator - Class in org.apache.commons.math.ode
- This class implements a Gragg-Bulirsch-Stoer integrator for
Ordinary Differential Equations.
- GraggBulirschStoerIntegrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.GraggBulirschStoerIntegrator
- Simple constructor.
- GraggBulirschStoerIntegrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.GraggBulirschStoerIntegrator
- Simple constructor.
- GraggBulirschStoerStepInterpolator - Class in org.apache.commons.math.ode
- This class implements an interpolator for the Gragg-Bulirsch-Stoer
integrator.
- GraggBulirschStoerStepInterpolator() -
Constructor for class org.apache.commons.math.ode.GraggBulirschStoerStepInterpolator
- Simple constructor.
- GraggBulirschStoerStepInterpolator(double[], double[], double[], double[], double[][], boolean) -
Constructor for class org.apache.commons.math.ode.GraggBulirschStoerStepInterpolator
- Simple constructor.
- GraggBulirschStoerStepInterpolator(GraggBulirschStoerStepInterpolator) -
Constructor for class org.apache.commons.math.ode.GraggBulirschStoerStepInterpolator
- Copy constructor.
- guessParametersErrors(EstimationProblem) -
Method in class org.apache.commons.math.estimation.AbstractEstimator
- Guess the errors in estimated parameters.
- guessParametersErrors(EstimationProblem) -
Method in interface org.apache.commons.math.estimation.Estimator
- Guess the errors in estimated parameters.
StatisticalSummary
instances, under the
assumption of equal subpopulation variances.
StatisticalSummary
instances, under the
assumption of equal subpopulation variances.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
, assuming that the
subpopulation variances are equal.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
, assuming that the
subpopulation variances are equal.
HypergeometricDistribution
.AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the input array.
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the specified portion of the input array.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
Double.POSITIVE_INFINITY
or
Double.NEGATIVE_INFINITY
) and neither part
is NaN
.
java.util.Random
to implement
RandomGenerator
.b
of x
.
MathConfigurationException.MathConfigurationException(String, Object[])
MathConfigurationException.MathConfigurationException(String, Object[], Throwable)
MathException
with no
detail message.
MathException.MathException(String, Object[])
MathException
with specified
formatted detail message.
MathException
with specified
nested Throwable
root cause.
MathException.MathException(String, Object[], Throwable)
MathException
with specified
formatted detail message and nested Throwable
root cause.
Math
.Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
m
.
m
.
addValue
method.UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
DistributionFactory
TestFactory
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
boolean
value from this random number generator's
sequence.
boolean
value from this random number generator's
sequence.
boolean
value from this random number generator's
sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
mean
.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
len
.
len
.
int
value from this random number generator's sequence.
int
value from this random number generator's sequence.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
int
value from this random number generator's sequence.
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
long
value from this random number generator's sequence.
k
whose entries
are selected randomly, without repetition, from the integers
0 through n-1
(inclusive).
k
objects selected randomly
from the Collection c
.
lower
and upper
(endpoints included)
from a secure random sequence.
lower
and upper
, inclusive.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
lower
,upper
) (i.e., endpoints excluded).
lower
,upper
) (i.e., endpoints excluded).
NormalDistribution
.OneWayAnovaImpl
interface.v
.
v
.
v
.
v
.
sample1
and
sample2
is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha
.
sample1
and
sample2
is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha
.
Complex
object.
Complex
object.
Fraction
object.
Fraction
object.
Fraction
object.
source
until a non-whitespace character is found.
source
until a non-whitespace character is found.
source
until a non-whitespace character is found.
source
until a non-whitespace character is found.
source
for a special double values.
source
for a number.
PascalDistribution
.p
th percentile of the values
in the values
array.
p
th percentile of the values
in the values
array, starting with the element in (0-based)
position begin
in the array and including length
values.
PointCostPair
objects.
PoissonDistribution
.x
.
y
value associated with the
supplied x
value, based on the data that has been
added to the model when this method is activated.
m
.
v
.
m
.
v
.
m
.
v
.
m
.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
java.util.Random
wrapping a
RandomGenerator
.RandomData
interface using a RandomGenerator
instance to generate non-secure data and a
SecureRandom
instance to provide data for the
nextSecureXxx
methods.RandomGenerator
as the source of (non-secure) random data.
java.util.Random
.v
as the
data for the unique column of the v.length x 1
matrix
created.
valuesFileURL
.
DoubleArray
implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed.d
d
expansionMode
.
DescriptiveStatistics.getPercentile(double)
.
long
seed.
long
seed.
long
seed.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
valuesFileURL
using a string URL representation
valuesFileURL
x
.
x
.
x
.
x
.
x
.
x
.
EstimationProblem
interface for boilerplate data handling.min
and max
.
startValue
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
this
2 for this complex
number.
isBiasCorrected
property.
isBiasCorrected
property and the supplied external moment.
FixedStepHandler
into a StepHandler
.UnivariateStatistic
with
StorelessUnivariateStatistic.increment(double)
and StorelessUnivariateStatistic.incrementAll(double[])
methods for adding
values and updating internal state.m
.
m
.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
addValue
method.SummaryStatistics
.Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
switching
functions
during integration.switching function
during integration steps.DescriptiveStatistics
that
is safe to use in a multithreaded environment.MultivariateSummaryStatistics
that
is safe to use in a multithreaded environment.SummaryStatistics
that
is safe to use in a multithreaded environment.sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
TDistribution
.evaluate(double[], int, int)
methods
to verify that the input parameters designate a subarray of positive length.
mu
.
sample
is drawn equals mu
.
sampleStats
with the constant mu
.
stats
is
drawn equals mu
.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
.
sampleStats1
and sampleStats2
describe
datasets drawn from populations with the same mean, with significance
level alpha
.
mu
.
sample
is drawn equals mu
.
sampleStats
with the constant mu
.
stats
is
drawn equals mu
.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
.
sampleStats1
and sampleStats2
describe
datasets drawn from populations with the same mean, with significance
level alpha
.
TTest
interface.RandomVectorGenerator
that generates vectors with uncorrelated
components.UnivariateRealSolver
instances.UnivariateRealSolverFactory
.UnivariateRealSolver
objects.isBiasCorrected
property.
isBiasCorrected
property
isBiasCorrected
property and the supplied external second moment.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
lower < initial < upper
throws IllegalArgumentException if not
WeibullDistribution
.
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