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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.
ChiSquareTest interface.ChiSquaredDistributionComplex arguments.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.
valuesFileURL after use in REPLAY_MODE.
valuesFileURL, using the default number of bins.
valuesFileURL and binCount bins.
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.
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).
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.
EmpiricalDistribution interface.ExponentialDistributionobject 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.
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.
FDistribution.length with values generated
using getNext() repeatedly.
Complex object to produce a string.
GammaDistributionDouble.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 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 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.
dimension x dimension identity matrix.
dimension x dimension identity matrix.
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.
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.
- 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.
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
UnivariateRealSolver for the given function.
UnivariateRealSolver for the given function.
UnivariateRealSolver for the given function.
UnivariateRealSolver for the given function.
mean.
len.
lower and upper (endpoints included).
lower and upper, inclusive.
lower and upper (endpoints included).
lower and upper, inclusive.
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.
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.
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.
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.
RandomData interface using
Random and Random.SecureRandom instances
to generate data.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.
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.
z2 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
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