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RandomGenerator
interface.StorelessUnivariateStatistic
interface.UnivariateStatistic
interface.m
.
m
.
data
.
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.
BinomialDistribution
.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.
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
.ChiSquareTest
interface.ChiSquaredDistribution
Complex
-valued functions.observed
and expected
freqeuncy counts.
counts
array, viewed as a two-way table.
observed
frequency counts to those in the expected
array.
alpha
.
counts
array, viewed as a two-way table.
alpha
.
AbstractRandomGenerator.nextGaussian()
.
valuesFileURL
after use in REPLAY_MODE.
valuesFileURL
, using the default number of bins.
valuesFileURL
and binCount
bins.
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.
- 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.
- doubleValue() -
Method in class org.apache.commons.math.fraction.Fraction
- Gets the fraction as a double.
EmpiricalDistribution
interface.ExponentialDistribution
.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
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.
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.
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.
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 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 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.
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.
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.
StatisticalSummaryValues
instance reporting current
statistics.
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 available values.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
- Returns the variance of the values that have been added.
- 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
- Univariate has the ability to return only measures for the
last N elements added to the set of values.
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
- Access the window size.
HypergeometricDistribution
.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.
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
.
Double.POSITIVE_INFINITY
or
Double.NEGATIVE_INFINITY
) and neither part
is NaN
.
java.util.Random
to implement
RandomGenerator
.MathException
with no
detail message.
MathException
with specified
detail message.
MathException
with specified
nested Throwable
root cause.
MathException
with specified
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
.
NormalDistribution
.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
DescriptiveStatistics
DescriptiveStatistics
SummaryStatistics
SummaryStatistics
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
.
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).
v
.
v
.
v
.
v
.
PoissonDistribution
.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.
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.
y
raised to the power of x
.
m
.
v
.
m
.
v
.
m
.
v
.
m
.
y
value associated with the
supplied x
value, based on the data that has been
added to the model when this method is activated.
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.
DoubleArray
implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed.valuesFileURL
.
isBiasCorrected
property.
isBiasCorrected
property and the supplied external moment.
UnivariateStatistic
with
StorelessUnivariateStatistic.increment(double)
and StorelessUnivariateStatistic.incrementAll(double[])
methods for adding
values and updating internal state.SummaryStatistics
implementation.d
d
expansionMode
.
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
.
min
and max
.
startValue
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
z
2 for the given complex
argument.
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.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
TDistribution
.TTest
interface.sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
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
.
evaluate(double[], int, int)
methods
to verify that the input parameters designate a subarray of positive length.
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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