Uses of Class
com.irurueta.numerical.NotReadyException

Packages that use NotReadyException

Package	Description
com.irurueta.numerical	This library contains packages for:
com.irurueta.numerical.fitting
com.irurueta.numerical.optimization
com.irurueta.numerical.polynomials.estimators
com.irurueta.numerical.robust	This package contains robust estimators that can be used to discard outliers for cases where a model of the data is known (i.e.
com.irurueta.numerical.roots	This package contains classes to find function roots.

Uses of NotReadyException in com.irurueta.numerical

Methods in com.irurueta.numerical that throw NotReadyException

Modifier and Type	Method	Description
double	AccurateMaximumLikelihoodEstimator.estimate()	Starts the estimation of the most likely value contained within provided input data array.
double	HistogramMaximumLikelihoodEstimator.estimate()	Starts the estimation of the most likely value contained within provided input data array.
abstract double	MaximumLikelihoodEstimator.estimate()	Starts the estimation of the most likely value contained within provided input data array.

Uses of NotReadyException in com.irurueta.numerical.fitting

Methods in com.irurueta.numerical.fitting that throw NotReadyException

Modifier and Type	Method	Description
abstract void	Fitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value
void	LevenbergMarquardtMultiDimensionFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.
void	LevenbergMarquardtMultiVariateFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.
void	LevenbergMarquardtSingleDimensionFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.
void	SimpleSingleDimensionLinearFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.
void	StraightLineFitter.fit()	Fits a straight line following equation y = a + b*x to provided data (x, y) so that parameters associated a, b can be estimated along with their variances, covariance and chi square value.
void	SvdMultiDimensionLinearFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.
void	SvdSingleDimensionLinearFitter.fit()	Fits a function to provided data so that parameters associated to that function can be estimated along with their covariance matrix and chi square value.

Uses of NotReadyException in com.irurueta.numerical.optimization

Methods in com.irurueta.numerical.optimization that throw NotReadyException

Modifier and Type	Method	Description
private void	PowellMultiOptimizer.buildDirections()	Internal method to build or rebuild the set of directions if needed.
void	BracketedSingleOptimizer.computeBracket()	Computes a bracket of values using the whole range of possible values as an initial guess.
void	BracketedSingleOptimizer.computeBracket(double minEvalPoint)	Computes a bracket of values using provided value as a starting point, and assuming that bracket finishes at Double.MAX_VALUE.
void	BracketedSingleOptimizer.computeBracket(double minEvalPoint, double middleEvalPoint)	Computes a bracket of values using provided values as a starting point.
void	BracketedSingleOptimizer.evaluateBracket()	Computes function evaluations at provided or estimated bracket locations.
void	BrentSingleOptimizer.minimize()	This function estimates a function minimum within provided or computed bracket of values.
void	ConjugateGradientMultiOptimizer.minimize()	This function estimates a function minimum.
void	DerivativeBrentSingleOptimizer.minimize()	This function estimates a function minimum within provided or computed bracket of values.
void	DerivativeConjugateGradientMultiOptimizer.minimize()	This function estimates a function minimum.
void	GoldenSingleOptimizer.minimize()	This function estimates a function minimum within provided or computed bracket of values.
void	Optimizer.minimize()	This function estimates a function minimum.
void	PowellMultiOptimizer.minimize()	This function estimates a function minimum.
void	QuasiNewtonMultiOptimizer.minimize()	This function estimates a function minimum.
void	SimplexMultiOptimizer.minimize()	This function estimates a function minimum.

Uses of NotReadyException in com.irurueta.numerical.polynomials.estimators

Methods in com.irurueta.numerical.polynomials.estimators that throw NotReadyException

Modifier and Type	Method	Description
Polynomial	LMedSPolynomialRobustEstimator.estimate()	Estimates polynomial.
Polynomial	LMSEPolynomialEstimator.estimate()	Estimates a polynomial based on provided evaluations.
Polynomial	MSACPolynomialRobustEstimator.estimate()	Estimates polynomial.
abstract Polynomial	PolynomialEstimator.estimate()	Estimates a polynomial based on provided evaluations.
abstract Polynomial	PolynomialRobustEstimator.estimate()	Estimates polynomial.
Polynomial	PROMedSPolynomialRobustEstimator.estimate()	Estimates polynomial.
Polynomial	PROSACPolynomialRobustEstimator.estimate()	Estimates polynomial.
Polynomial	RANSACPolynomialRobustEstimator.estimate()	Estimates polynomial.
Polynomial	WeightedPolynomialEstimator.estimate()	Estimates a polynomial based on provided evaluations.

Uses of NotReadyException in com.irurueta.numerical.robust

Methods in com.irurueta.numerical.robust that throw NotReadyException

Modifier and Type	Method	Description
T	LMedSRobustEstimator.estimate()	Robustly estimates an instance of T.
T	MSACRobustEstimator.estimate()	Robustly estimates an instance of T.
T	PROMedSRobustEstimator.estimate()	Robustly estimates an instance of T.
T	PROSACRobustEstimator.estimate()	Robustly estimates an instance of T.
T	RANSACRobustEstimator.estimate()	Robustly estimates an instance of T.
abstract T	RobustEstimator.estimate()	Robustly estimates an instance of T.

Uses of NotReadyException in com.irurueta.numerical.roots

Methods in com.irurueta.numerical.roots that throw NotReadyException

Modifier and Type	Method	Description
void	BracketedSingleRootEstimator.computeBracket()	Starting at zero, this method expands the range (i.e.
void	BracketedSingleRootEstimator.computeBracket(double point)	Starting from provided point, this method expands the range (i.e.
void	BracketedSingleRootEstimator.computeBracket(double minEvalPoint, double maxEvalPoint)	Starting from provided minimum and maximum values, this method expands the range (i.e.
void	BisectionSingleRootEstimator.estimate()	Estimates a single root of the provided single dimension function contained within a given bracket of values.
void	BrentSingleRootEstimator.estimate()	Estimates a local root for a given single dimension function being evaluated by provided listener.
void	FalsePositionSingleRootEstimator.estimate()	Estimates a single root of the provided single dimension function contained within a given bracket of values.
void	FirstDegreePolynomialRootsEstimator.estimate()	Estimates the root of provided polynomial.
void	LaguerrePolynomialRootsEstimator.estimate()	Estimates the roots of provided polynomial.
void	NewtonRaphsonSingleRootEstimator.estimate()	Estimates a local root for a given single dimension function being evaluated by provided listener.
void	RidderSingleRootEstimator.estimate()	Estimates a local root for a given single dimension function being evaluated by provided listener.
void	RootEstimator.estimate()	Estimates the root or roots for a given function.
void	SafeNewtonRaphsonSingleRootEstimator.estimate()	Estimates a local root for a given single dimension function being evaluated by provided listener.
void	SecantSingleRootEstimator.estimate()	Estimates a local root for a given single dimension function being evaluated by provided listener.
void	SecondDegreePolynomialRootsEstimator.estimate()	Estimates the roots of provided polynomial.
void	ThirdDegreePolynomialRootsEstimator.estimate()	Estimates the roots of provided polynomial.
boolean	SecondDegreePolynomialRootsEstimator.hasDoubleRoot()	Returns boolean indicating whether this second degree polynomial has multiple roots (for the 2nd degree case this means 2 equal roots) This is true for polynomials of the form (x - r)^2 = x^2 - 2 * r * x + r^2, where r is the double root
boolean	ThirdDegreePolynomialRootsEstimator.hasMultipleRealRoot()	Returns boolean indicating whether the polynomial has two real and equal roots and a third different one (multiplicity 2), or all three roots are real and equal (multiplicity 3).
boolean	ThirdDegreePolynomialRootsEstimator.hasOneRealRootAndTwoComplexConjugateRoots()	Returns boolean indicating whether the polynomial has one real root and two complex conjugate roots.
boolean	ThirdDegreePolynomialRootsEstimator.hasThreeDistinctRealRoots()	Returns boolean indicating whether the roots of the polynomial are three distinct and real roots or not.
boolean	SecondDegreePolynomialRootsEstimator.hasTwoComplexConjugateRoots()	Returns boolean indicating whether the roots of the polynomial are two complex conjugate roots or not.
boolean	SecondDegreePolynomialRootsEstimator.hasTwoDistinctRealRoots()	Returns boolean indicating whether the roots of the polynomial are two distinct and real roots or not.
boolean	FirstDegreePolynomialRootsEstimator.isFirstDegree()	Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid first degree polynomial.
boolean	SecondDegreePolynomialRootsEstimator.isSecondDegree()	Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid second degree polynomial.
boolean	ThirdDegreePolynomialRootsEstimator.isThirdDegree()	Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid third degree polynomial.