Package | Description |
---|---|
org.apache.commons.math3.analysis.integration |
Numerical integration (quadrature) algorithms for univariate real functions.
|
org.apache.commons.math3.exception |
Specialized exceptions for algorithms errors.
|
org.apache.commons.math3.linear |
Linear algebra support.
|
org.apache.commons.math3.ode |
This package provides classes to solve Ordinary Differential Equations problems.
|
org.apache.commons.math3.ode.events |
This package provides classes to handle discrete events occurring during
Ordinary Differential Equations integration.
|
org.apache.commons.math3.ode.nonstiff |
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
|
org.apache.commons.math3.ode.sampling |
This package provides classes to handle sampling steps during
Ordinary Differential Equations integration.
|
org.apache.commons.math3.optimization.linear |
This package provides optimization algorithms for linear constrained problems.
|
org.apache.commons.math3.stat.inference |
Classes providing hypothesis testing.
|
org.apache.commons.math3.util |
Convenience routines and common data structures used throughout the commons-math library.
|
Modifier and Type | Method and Description |
---|---|
protected double |
IterativeLegendreGaussIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
RombergIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected abstract double |
BaseAbstractUnivariateIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
TrapezoidIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
LegendreGaussIntegrator.doIntegrate()
Deprecated.
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
SimpsonIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
MidPointIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected void |
BaseAbstractUnivariateIntegrator.incrementCount()
Increment the number of iterations.
|
double |
UnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double min,
double max)
Integrate the function in the given interval.
|
double |
BaseAbstractUnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double lower,
double upper)
Integrate the function in the given interval.
|
Modifier and Type | Class and Description |
---|---|
class |
TooManyEvaluationsException
Exception to be thrown when the maximal number of evaluations is exceeded.
|
class |
TooManyIterationsException
Exception to be thrown when the maximal number of iterations is exceeded.
|
Modifier and Type | Method and Description |
---|---|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
boolean goodb,
double shift)
Returns an estimate of the solution to the linear system (A - shift
· I) · x = b.
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealVector b)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
IterativeLinearSolver.solve(RealLinearOperator a,
RealVector b)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealVector b)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealVector b,
boolean goodb,
double shift)
Returns the solution to the system (A - shift · I) · x = b.
|
RealVector |
SymmLQ.solve(RealLinearOperator a,
RealVector b,
RealVector x)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
IterativeLinearSolver.solve(RealLinearOperator a,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
PreconditionedIterativeLinearSolver.solve(RealLinearOperator a,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
SymmLQ.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
ConjugateGradient.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
abstract RealVector |
PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
SymmLQ.solveInPlace(RealLinearOperator a,
RealLinearOperator m,
RealVector b,
RealVector x,
boolean goodb,
double shift)
Returns an estimate of the solution to the linear system (A - shift
· I) · x = b.
|
RealVector |
SymmLQ.solveInPlace(RealLinearOperator a,
RealVector b,
RealVector x)
Returns an estimate of the solution to the linear system A · x =
b.
|
abstract RealVector |
IterativeLinearSolver.solveInPlace(RealLinearOperator a,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
RealVector |
PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a,
RealVector b,
RealVector x0)
Returns an estimate of the solution to the linear system A · x =
b.
|
Modifier and Type | Method and Description |
---|---|
protected FieldODEStateAndDerivative<T> |
AbstractFieldIntegrator.acceptStep(AbstractFieldStepInterpolator<T> interpolator,
T tEnd)
Accept a step, triggering events and step handlers.
|
protected double |
AbstractIntegrator.acceptStep(AbstractStepInterpolator interpolator,
double[] y,
double[] yDot,
double tEnd)
Accept a step, triggering events and step handlers.
|
void |
ContinuousOutputFieldModel.append(ContinuousOutputFieldModel<T> model)
Append another model at the end of the instance.
|
void |
ContinuousOutputModel.append(ContinuousOutputModel model)
Append another model at the end of the instance.
|
void |
FirstOrderDifferentialEquations.computeDerivatives(double t,
double[] y,
double[] yDot)
Get the current time derivative of the state vector.
|
void |
ExpandableStatefulODE.computeDerivatives(double t,
double[] y,
double[] yDot)
Get the current time derivative of the complete state vector.
|
void |
AbstractIntegrator.computeDerivatives(double t,
double[] y,
double[] yDot)
Compute the derivatives and check the number of evaluations.
|
void |
SecondaryEquations.computeDerivatives(double t,
double[] primary,
double[] primaryDot,
double[] secondary,
double[] secondaryDot)
Compute the derivatives related to the secondary state parameters.
|
T[] |
AbstractFieldIntegrator.computeDerivatives(T t,
T[] y)
Compute the derivatives and check the number of evaluations.
|
T[] |
FieldExpandableODE.computeDerivatives(T t,
T[] y)
Get the current time derivative of the complete state vector.
|
T[] |
FieldSecondaryEquations.computeDerivatives(T t,
T[] primary,
T[] primaryDot,
T[] secondary)
Compute the derivatives related to the secondary state parameters.
|
void |
MainStateJacobianProvider.computeMainStateJacobian(double t,
double[] y,
double[] yDot,
double[][] dFdY)
Compute the jacobian matrix of ODE with respect to main state.
|
void |
ParameterJacobianProvider.computeParameterJacobian(double t,
double[] y,
double[] yDot,
String paramName,
double[] dFdP)
Compute the Jacobian matrix of ODE with respect to one parameter.
|
double[] |
ContinuousOutputModel.getInterpolatedDerivatives()
Get the derivatives of the state vector of the interpolated point.
|
double[] |
ContinuousOutputModel.getInterpolatedSecondaryDerivatives(int secondaryStateIndex)
Get the interpolated secondary derivatives corresponding to the secondary equations.
|
double[] |
ContinuousOutputModel.getInterpolatedSecondaryState(int secondaryStateIndex)
Get the interpolated secondary state corresponding to the secondary equations.
|
double[] |
ContinuousOutputModel.getInterpolatedState()
Get the state vector of the interpolated point.
|
void |
ContinuousOutputFieldModel.handleStep(FieldStepInterpolator<T> interpolator,
boolean isLast)
Handle the last accepted step.
|
void |
ContinuousOutputModel.handleStep(StepInterpolator interpolator,
boolean isLast)
Handle the last accepted step.
|
abstract void |
AbstractIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
FirstOrderFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
double |
FirstOrderIntegrator.integrate(FirstOrderDifferentialEquations equations,
double t0,
double[] y0,
double t,
double[] y)
Integrate the differential equations up to the given time.
|
double |
AbstractIntegrator.integrate(FirstOrderDifferentialEquations equations,
double t0,
double[] y0,
double t,
double[] y)
Integrate the differential equations up to the given time.
|
protected void |
MultistepIntegrator.start(double t0,
double[] y0,
double t)
Start the integration.
|
protected void |
MultistepFieldIntegrator.start(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T t)
Start the integration.
|
Modifier and Type | Method and Description |
---|---|
boolean |
FieldEventState.evaluateStep(FieldStepInterpolator<T> interpolator)
Evaluate the impact of the proposed step on the event handler.
|
boolean |
EventState.evaluateStep(StepInterpolator interpolator)
Evaluate the impact of the proposed step on the event handler.
|
void |
FieldEventState.reinitializeBegin(FieldStepInterpolator<T> interpolator)
Reinitialize the beginning of the step.
|
void |
EventState.reinitializeBegin(StepInterpolator interpolator)
Reinitialize the beginning of the step.
|
Modifier and Type | Method and Description |
---|---|
double |
AdaptiveStepsizeIntegrator.initializeStep(boolean forward,
int order,
double[] scale,
double t0,
double[] y0,
double[] yDot0,
double[] y1,
double[] yDot1)
Initialize the integration step.
|
T |
AdaptiveStepsizeFieldIntegrator.initializeStep(boolean forward,
int order,
T[] scale,
FieldODEStateAndDerivative<T> state0,
FieldEquationsMapper<T> mapper)
Initialize the integration step.
|
abstract void |
AdamsIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
abstract void |
AdaptiveStepsizeIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
AdamsMoultonIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
EmbeddedRungeKuttaIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
AdamsBashforthIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
RungeKuttaIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
GraggBulirschStoerIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
RungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
EmbeddedRungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
AdamsBashforthFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
AdamsMoultonFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
abstract FieldODEStateAndDerivative<T> |
AdamsFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
Modifier and Type | Method and Description |
---|---|
protected abstract void |
AbstractStepInterpolator.computeInterpolatedStateAndDerivatives(double theta,
double oneMinusThetaH)
Compute the state and derivatives at the interpolated time.
|
protected abstract FieldODEStateAndDerivative<T> |
AbstractFieldStepInterpolator.computeInterpolatedStateAndDerivatives(FieldEquationsMapper<T> equationsMapper,
T time,
T theta,
T thetaH,
T oneMinusThetaH)
Compute the state and derivatives at the interpolated time.
|
StepInterpolator |
AbstractStepInterpolator.copy()
Copy the instance.
|
StepInterpolator |
StepInterpolator.copy()
Copy the instance.
|
protected void |
AbstractStepInterpolator.doFinalize()
Really finalize the step.
|
void |
AbstractStepInterpolator.finalizeStep()
Finalize the step.
|
double[] |
AbstractStepInterpolator.getInterpolatedDerivatives()
Get the derivatives of the state vector of the interpolated point.
|
double[] |
StepInterpolator.getInterpolatedDerivatives()
Get the derivatives of the state vector of the interpolated point.
|
double[] |
AbstractStepInterpolator.getInterpolatedSecondaryDerivatives(int index)
Get the interpolated secondary derivatives corresponding to the secondary equations.
|
double[] |
StepInterpolator.getInterpolatedSecondaryDerivatives(int index)
Get the interpolated secondary derivatives corresponding to the secondary equations.
|
double[] |
AbstractStepInterpolator.getInterpolatedSecondaryState(int index)
Get the interpolated secondary state corresponding to the secondary equations.
|
double[] |
StepInterpolator.getInterpolatedSecondaryState(int index)
Get the interpolated secondary state corresponding to the secondary equations.
|
double[] |
AbstractStepInterpolator.getInterpolatedState()
Get the state vector of the interpolated point.
|
double[] |
StepInterpolator.getInterpolatedState()
Get the state vector of the interpolated point.
|
double[] |
NordsieckStepInterpolator.getInterpolatedStateVariation()
Get the state vector variation from current to interpolated state.
|
void |
FieldStepNormalizer.handleStep(FieldStepInterpolator<T> interpolator,
boolean isLast)
Handle the last accepted step
|
void |
FieldStepHandler.handleStep(FieldStepInterpolator<T> interpolator,
boolean isLast)
Handle the last accepted step
|
void |
StepNormalizer.handleStep(StepInterpolator interpolator,
boolean isLast)
Handle the last accepted step
|
void |
StepHandler.handleStep(StepInterpolator interpolator,
boolean isLast)
Handle the last accepted step
|
Modifier and Type | Method and Description |
---|---|
protected void |
SimplexSolver.doIteration(org.apache.commons.math3.optimization.linear.SimplexTableau tableau)
Deprecated.
Runs one iteration of the Simplex method on the given model.
|
PointValuePair |
SimplexSolver.doOptimize()
Deprecated.
Perform the bulk of optimization algorithm.
|
protected void |
AbstractLinearOptimizer.incrementIterationsCounter()
Deprecated.
Increment the iterations counter by 1.
|
protected void |
SimplexSolver.solvePhase1(org.apache.commons.math3.optimization.linear.SimplexTableau tableau)
Deprecated.
Solves Phase 1 of the Simplex method.
|
Modifier and Type | Method and Description |
---|---|
double |
OneWayAnova.anovaPValue(Collection<double[]> categoryData)
Computes the ANOVA P-value for a collection of
double[]
arrays. |
double |
OneWayAnova.anovaPValue(Collection<SummaryStatistics> categoryData,
boolean allowOneElementData)
Computes the ANOVA P-value for a collection of
SummaryStatistics . |
boolean |
OneWayAnova.anovaTest(Collection<double[]> categoryData,
double alpha)
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
|
static double |
TestUtils.chiSquareTest(double[] expected,
long[] observed) |
double |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or
p-value, associated with a
Chi-square goodness of fit test comparing the
observed
frequency counts to those in the expected array. |
static boolean |
TestUtils.chiSquareTest(double[] expected,
long[] observed,
double alpha) |
boolean |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a
Chi-square goodness of fit test evaluating the null hypothesis that the
observed counts conform to the frequency distribution described by the expected
counts, with significance level
alpha . |
static double |
TestUtils.chiSquareTest(long[][] counts) |
double |
ChiSquareTest.chiSquareTest(long[][] counts)
Returns the observed significance level, or
p-value, associated with a
chi-square test of independence based on the input
counts
array, viewed as a two-way table. |
static boolean |
TestUtils.chiSquareTest(long[][] counts,
double alpha) |
boolean |
ChiSquareTest.chiSquareTest(long[][] counts,
double alpha)
Performs a
chi-square test of independence evaluating the null hypothesis that the
classifications represented by the counts in the columns of the input 2-way table
are independent of the rows, with significance level
alpha . |
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.gTest(double[] expected,
long[] observed) |
double |
GTest.gTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value,
associated with a G-Test for goodness of fit comparing the
observed frequency counts to those in the expected array. |
static boolean |
TestUtils.gTest(double[] expected,
long[] observed,
double alpha) |
boolean |
GTest.gTest(double[] expected,
long[] observed,
double alpha)
Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit
evaluating the null hypothesis that the observed counts conform to the
frequency distribution described by the expected counts, with
significance level
alpha . |
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.gTestIntrinsic(double[] expected,
long[] observed) |
double |
GTest.gTestIntrinsic(double[] expected,
long[] observed)
Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described
in p64-69 of McDonald, J.H.
|
static double |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2) |
double |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the input arrays, under the assumption that
the two samples are drawn from subpopulations with equal variances.
|
static boolean |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha , assuming that the
subpopulation variances are equal. |
protected double |
TTest.homoscedasticTTest(double m1,
double m2,
double v1,
double v2,
double n1,
double n2)
Computes p-value for 2-sided, 2-sample t-test, under the assumption
of equal subpopulation variances.
|
static double |
TestUtils.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the datasets described by two StatisticalSummary
instances, under the hypothesis of equal subpopulation variances.
|
double |
MannWhitneyUTest.mannWhitneyUTest(double[] x,
double[] y)
Returns the asymptotic observed significance level, or
p-value, associated with a Mann-Whitney
U statistic comparing mean for two independent samples.
|
static double |
TestUtils.oneWayAnovaPValue(Collection<double[]> categoryData) |
static boolean |
TestUtils.oneWayAnovaTest(Collection<double[]> categoryData,
double alpha) |
static double |
TestUtils.pairedTTest(double[] sample1,
double[] sample2) |
double |
TTest.pairedTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a paired, two-sample, two-tailed t-test
based on the data in the input arrays.
|
static boolean |
TestUtils.pairedTTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a paired t-test evaluating the null hypothesis that the
mean of the paired differences between
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 . |
static double |
TestUtils.tTest(double[] sample1,
double[] sample2) |
double |
TTest.tTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the input arrays.
|
static boolean |
TestUtils.tTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.tTest(double[] sample1,
double[] sample2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha . |
static double |
TestUtils.tTest(double mu,
double[] sample) |
double |
TTest.tTest(double mu,
double[] sample)
Returns the observed significance level, or
p-value, associated with a one-sample, two-tailed t-test
comparing the mean of the input array with the constant
mu . |
static boolean |
TestUtils.tTest(double mu,
double[] sample,
double alpha) |
boolean |
TTest.tTest(double mu,
double[] sample,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that the mean of the population from
which
sample is drawn equals mu . |
protected double |
TTest.tTest(double m,
double mu,
double v,
double n)
Computes p-value for 2-sided, 1-sample t-test.
|
protected double |
TTest.tTest(double m1,
double m2,
double v1,
double v2,
double n1,
double n2)
Computes p-value for 2-sided, 2-sample t-test.
|
static double |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats) |
double |
TTest.tTest(double mu,
StatisticalSummary sampleStats)
Returns the observed significance level, or
p-value, associated with a one-sample, two-tailed t-test
comparing the mean of the dataset described by
sampleStats
with the constant mu . |
static boolean |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats,
double alpha) |
boolean |
TTest.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that the mean of the
population from which the dataset described by
stats is
drawn equals mu . |
static double |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the datasets described by two StatisticalSummary
instances.
|
static boolean |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha) |
boolean |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sampleStats1 and sampleStats2 describe
datasets drawn from populations with the same mean, with significance
level alpha . |
double |
WilcoxonSignedRankTest.wilcoxonSignedRankTest(double[] x,
double[] y,
boolean exactPValue)
Returns the observed significance level, or
p-value, associated with a
Wilcoxon signed ranked statistic comparing mean for two related
samples or repeated measurements on a single sample.
|
Modifier and Type | Method and Description |
---|---|
double |
ContinuedFraction.evaluate(double x,
double epsilon,
int maxIterations)
Evaluates the continued fraction at the value x.
|
double |
ContinuedFraction.evaluate(double x,
int maxIterations)
Evaluates the continued fraction at the value x.
|
void |
IntegerSequence.Incrementor.increment()
Adds the increment value to the current iteration count.
|
void |
IntegerSequence.Incrementor.increment(int nTimes)
Performs multiple increments.
|
void |
Incrementor.incrementCount()
Deprecated.
Adds one to the current iteration count.
|
void |
Incrementor.incrementCount(int value)
Deprecated.
Performs multiple increments.
|
void |
IterationManager.incrementIterationCount()
Increments the iteration count by one, and throws an exception if the
maximum number of iterations is reached.
|
void |
Incrementor.MaxCountExceededCallback.trigger(int maximalCount)
Function called when the maximal count has been reached.
|
void |
IntegerSequence.Incrementor.MaxCountExceededCallback.trigger(int maximalCount)
Function called when the maximal count has been reached.
|
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