Package | Description |
---|---|
org.apache.commons.math3.analysis.interpolation |
Univariate real functions interpolation algorithms.
|
org.apache.commons.math3.complex |
Complex number type and implementations of complex transcendental
functions.
|
org.apache.commons.math3.linear |
Linear algebra support.
|
org.apache.commons.math3.random |
Random number and random data generators.
|
org.apache.commons.math3.stat.inference |
Classes providing hypothesis testing.
|
Modifier and Type | Method and Description |
---|---|
void |
HermiteInterpolator.addSamplePoint(double x,
double[]... value)
Add a sample point.
|
void |
FieldHermiteInterpolator.addSamplePoint(T x,
T[]... value)
Add a sample point.
|
Modifier and Type | Method and Description |
---|---|
void |
RootsOfUnity.computeRoots(int n)
Computes the
n -th roots of unity. |
Modifier and Type | Method and Description |
---|---|
static <T extends FieldElement<T>> |
MatrixUtils.createFieldVector(T[] data)
Creates a
FieldVector using the data from the input array. |
Constructor and Description |
---|
ArrayFieldVector(Field<T> field,
T[] v1,
T[] v2)
Construct a vector by appending one vector to another vector.
|
ArrayFieldVector(T[] d)
Construct a vector from an array, copying the input array.
|
ArrayFieldVector(T[] d,
boolean copyArray)
Create a new ArrayFieldVector using the input array as the underlying
data array.
|
ArrayFieldVector(T[] v1,
T[] v2)
Construct a vector by appending one vector to another vector.
|
Modifier and Type | Method and Description |
---|---|
void |
ValueServer.computeDistribution()
Computes the empirical distribution using values from the file
in
valuesFileURL , using the default number of bins. |
void |
ValueServer.computeDistribution(int binCount)
Computes the empirical distribution using values from the file
in
valuesFileURL and binCount bins. |
void |
EmpiricalDistribution.load(URL url)
Computes the empirical distribution using data read from a URL.
|
Modifier and Type | Method and Description |
---|---|
static double |
TestUtils.chiSquareDataSetsComparison(long[] observed1,
long[] observed2) |
double |
ChiSquareTest.chiSquareDataSetsComparison(long[] observed1,
long[] observed2)
Computes a
Chi-Square two sample test statistic comparing bin frequency counts
in
observed1 and observed2 . |
static double |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2) |
double |
ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
Returns the observed significance level, or
p-value, associated with a Chi-Square two sample test comparing
bin frequency counts in
observed1 and
observed2 . |
static boolean |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha) |
boolean |
ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
Performs a Chi-Square two sample test comparing two binned data
sets.
|
static double |
TestUtils.gDataSetsComparison(long[] observed1,
long[] observed2) |
double |
GTest.gDataSetsComparison(long[] observed1,
long[] observed2)
Computes a G (Log-Likelihood Ratio) two sample test statistic for
independence comparing frequency counts in
observed1 and observed2 . |
static double |
TestUtils.gTestDataSetsComparison(long[] observed1,
long[] observed2) |
double |
GTest.gTestDataSetsComparison(long[] observed1,
long[] observed2)
Returns the observed significance level, or
p-value, associated with a G-Value (Log-Likelihood Ratio) for two
sample test comparing bin frequency counts in
observed1 and
observed2 . |
static boolean |
TestUtils.gTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha) |
boolean |
GTest.gTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned
data sets.
|
static double |
TestUtils.rootLogLikelihoodRatio(long k11,
long k12,
long k21,
long k22) |
Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.