|
||||||||||
| PREV NEXT | FRAMES NO FRAMES | |||||||||
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.
ChiSquaredDistributionobserved
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.
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).
DescriptiveStatisticsUnivariateRealFunction 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.
- 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.DummyStepInterpolator
- Really copy the finalized instance.
- doFinalize() -
Method in class org.apache.commons.math.ode.AbstractStepInterpolator
- 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.
- 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.
- 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.
- 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.object 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.
pth percentile of the values
in the values array.
quantileth percentile of the
designated values in the values array.
pth 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.
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.
- 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.
- 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.
PascalDistribution.pth percentile of the values
in the values array.
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values.
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.
this2 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.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.
|
||||||||||
| PREV NEXT | FRAMES NO FRAMES | |||||||||