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## Uses of Class
org.apache.commons.math3.exception.MaxCountExceededException

Packages that use MaxCountExceededException
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 and confidence interval construction.
org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library.

Uses of MaxCountExceededException in org.apache.commons.math3.analysis.integration

Methods in org.apache.commons.math3.analysis.integration that throw MaxCountExceededException
`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` | `SimpsonIntegrator.doIntegrate()` Method for implementing actual integration algorithms in derived classes.
`protected double` | `IterativeLegendreGaussIntegrator.doIntegrate()` Method for implementing actual integration algorithms in derived classes.
`protected double` | `LegendreGaussIntegrator.doIntegrate()` Deprecated. Method for implementing actual integration algorithms in derived classes.
`double` | `BaseAbstractUnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double lower, double upper)` Integrate the function in the given interval.
`double` | `UnivariateIntegrator.integrate(int maxEval, UnivariateFunction f, double min, double max)` Integrate the function in the given interval.

Uses of MaxCountExceededException in org.apache.commons.math3.exception

Subclasses of MaxCountExceededException in org.apache.commons.math3.exception
`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.

Uses of MaxCountExceededException in org.apache.commons.math3.linear

Methods in org.apache.commons.math3.linear that throw MaxCountExceededException
`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)` 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` | `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, RealLinearOperator m, RealVector b, RealVector x)` 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` | `IterativeLinearSolver.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)` 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` | `PreconditionedIterativeLinearSolver.solve(RealLinearOperator a, RealVector b, RealVector x0)` 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` | `SymmLQ.solve(RealLinearOperator a, 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)` 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` | `PreconditionedIterativeLinearSolver.solveInPlace(RealLinearOperator a, RealVector b, RealVector x0)` 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` | `SymmLQ.solveInPlace(RealLinearOperator a, RealVector b, RealVector x)` Returns an estimate of the solution to the linear system A · x = b.

Uses of MaxCountExceededException in org.apache.commons.math3.ode

Methods in org.apache.commons.math3.ode that throw MaxCountExceededException
`protected double` | `AbstractIntegrator.acceptStep(AbstractStepInterpolator interpolator, double[] y, double[] yDot, double tEnd)` Accept a step, triggering events and step handlers.
`void` | `ContinuousOutputModel.append(ContinuousOutputModel model)` Append another model at the end of the instance.
`void` | `AbstractIntegrator.computeDerivatives(double t, double[] y, double[] yDot)` Compute the derivatives and check the number of evaluations.
`void` | `ExpandableStatefulODE.computeDerivatives(double t, double[] y, double[] yDot)` Get the current time derivative of the complete state vector.
`void` | `FirstOrderDifferentialEquations.computeDerivatives(double t, double[] y, double[] yDot)` Get the current time derivative of the state vector.
`void` | `SecondaryEquations.computeDerivatives(double t, double[] primary, double[] primaryDot, double[] secondary, double[] secondaryDot)` 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.getInterpolatedState()` Get the state vector of the interpolated point.
`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.
`double` | `AbstractIntegrator.integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)` 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.
`protected void` | `MultistepIntegrator.start(double t0, double[] y0, double t)` Start the integration.

Uses of MaxCountExceededException in org.apache.commons.math3.ode.events

Methods in org.apache.commons.math3.ode.events that throw MaxCountExceededException
`boolean` | `EventState.evaluateStep(StepInterpolator interpolator)` Evaluate the impact of the proposed step on the event handler.
`void` | `EventState.reinitializeBegin(StepInterpolator interpolator)` Reinitialize the beginning of the step.

Uses of MaxCountExceededException in org.apache.commons.math3.ode.nonstiff

Methods in org.apache.commons.math3.ode.nonstiff that throw MaxCountExceededException
`double` | `AdaptiveStepsizeIntegrator.initializeStep(boolean forward, int order, double[] scale, double t0, double[] y0, double[] yDot0, double[] y1, double[] yDot1)` Initialize the integration step.
`abstract void` | `AdamsIntegrator.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.
`abstract void` | `AdaptiveStepsizeIntegrator.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.
`void` | `EmbeddedRungeKuttaIntegrator.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` | `RungeKuttaIntegrator.integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.

Uses of MaxCountExceededException in org.apache.commons.math3.ode.sampling

Methods in org.apache.commons.math3.ode.sampling that throw MaxCountExceededException
`protected abstract void` | `AbstractStepInterpolator.computeInterpolatedStateAndDerivatives(double theta, double oneMinusThetaH)` Compute the state and derivatives at the interpolated time.
`StepInterpolator` | `StepInterpolator.copy()` Copy the instance.
`StepInterpolator` | `AbstractStepInterpolator.copy()` Copy the instance.
`protected void` | `AbstractStepInterpolator.doFinalize()` Really finalize the step.
`void` | `AbstractStepInterpolator.finalizeStep()` Finalize the step.
`double[]` | `StepInterpolator.getInterpolatedDerivatives()` Get the derivatives of the state vector of the interpolated point.
`double[]` | `AbstractStepInterpolator.getInterpolatedDerivatives()` Get the derivatives of the state vector of the interpolated point.
`double[]` | `StepInterpolator.getInterpolatedSecondaryDerivatives(int index)` Get the interpolated secondary derivatives corresponding to the secondary equations.
`double[]` | `AbstractStepInterpolator.getInterpolatedSecondaryDerivatives(int index)` Get the interpolated secondary derivatives corresponding to the secondary equations.
`double[]` | `StepInterpolator.getInterpolatedSecondaryState(int index)` Get the interpolated secondary state corresponding to the secondary equations.
`double[]` | `AbstractStepInterpolator.getInterpolatedSecondaryState(int index)` Get the interpolated secondary state corresponding to the secondary equations.
`double[]` | `StepInterpolator.getInterpolatedState()` Get the state vector of the interpolated point.
`double[]` | `AbstractStepInterpolator.getInterpolatedState()` Get the state vector of the interpolated point.
`double[]` | `NordsieckStepInterpolator.getInterpolatedStateVariation()` Get the state vector variation from current to interpolated state.
`void` | `StepHandler.handleStep(StepInterpolator interpolator, boolean isLast)` Handle the last accepted step
`void` | `StepNormalizer.handleStep(StepInterpolator interpolator, boolean isLast)` Handle the last accepted step

Uses of MaxCountExceededException in org.apache.commons.math3.optimization.linear

Methods in org.apache.commons.math3.optimization.linear that throw MaxCountExceededException
`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.

Uses of MaxCountExceededException in org.apache.commons.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that throw MaxCountExceededException
`double` | `OneWayAnova.anovaPValue(Collection<double[]> categoryData)` Computes the ANOVA P-value for a collection of `double[]` arrays.
`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.

Uses of MaxCountExceededException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw MaxCountExceededException
`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` | `IterationManager.incrementIterationCount()` Increments the iteration count by one, and throws an exception if the maximum number of iterations is reached.

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