Uses of Class
org.hipparchus.exception.MathIllegalStateException

Packages that use MathIllegalStateException
Package
Description
Numerical integration (quadrature) algorithms for univariate real functions.
Root finding algorithms, for univariate real functions.
Clustering algorithms.
Complex number type and implementations of complex transcendental functions.
Fraction number type and fraction number formatting.
This package is the top level package for geometry.
This package provides basic 1D geometry components.
This package provides basic 3D geometry components.
This package provides basic 2D geometry components.
This package provides algorithms to generate the convex hull for a set of points in an two-dimensional euclidean space.
This package provides interfaces and classes related to the convex hull problem.
This package provides basic geometry components on the 2-sphere.
Linear algebra support.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides migration classes from Apache Commons Math to Hipparchus.
This package provides classes to solve Ordinary Differential Equations problems.
Events
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
This package provides classes to handle sampling steps during Ordinary Differential Equations integration.
Generally, optimizers are algorithms that will either minimize or maximize a scalar function, called the objective function.
Optimization algorithms for linear constrained problems.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that require derivatives.
This package provides optimization algorithms that do not require derivatives.
This package provides algorithms that minimize the residuals between observations and model values.
One-dimensional optimization algorithms.
Random number and random data generators.
Implementations of special functions such as Beta and Gamma.
Generic univariate and multivariate summary statistic objects.
Statistical methods for fitting distributions.
Classes providing hypothesis testing.
Convenience routines and common data structures used throughout the Hipparchus library.