Uses of Class
com.irurueta.numerical.NotReadyException
Packages that use NotReadyException
Package
Description
This library contains packages for:
This package contains robust estimators that can be used to discard outliers
for cases where a model of the data is known (i.e. estimating lines, planes
or many other geometric objects, etc.)
This package contains classes to find function roots.
-
Uses of NotReadyException in com.irurueta.numerical
Methods in com.irurueta.numerical that throw NotReadyExceptionModifier and TypeMethodDescriptiondoubleAccurateMaximumLikelihoodEstimator.estimate()Starts the estimation of the most likely value contained within provided input data array.doubleHistogramMaximumLikelihoodEstimator.estimate()Starts the estimation of the most likely value contained within provided input data array.abstract doubleMaximumLikelihoodEstimator.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 NotReadyExceptionModifier and TypeMethodDescriptionabstract voidFitter.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 valuevoidLevenbergMarquardtMultiDimensionFitter.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.voidLevenbergMarquardtMultiVariateFitter.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.voidLevenbergMarquardtSingleDimensionFitter.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.voidSimpleSingleDimensionLinearFitter.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.voidStraightLineFitter.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.voidSvdMultiDimensionLinearFitter.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.voidSvdSingleDimensionLinearFitter.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 NotReadyExceptionModifier and TypeMethodDescriptionprivate voidPowellMultiOptimizer.buildDirections()Internal method to build or rebuild the set of directions if needed.voidBracketedSingleOptimizer.computeBracket()Computes a bracket of values using the whole range of possible values as an initial guess.voidBracketedSingleOptimizer.computeBracket(double minEvalPoint) Computes a bracket of values using provided value as a starting point, and assuming that bracket finishes at Double.MAX_VALUE.voidBracketedSingleOptimizer.computeBracket(double minEvalPoint, double middleEvalPoint) Computes a bracket of values using provided values as a starting point.voidBracketedSingleOptimizer.evaluateBracket()Computes function evaluations at provided or estimated bracket locations.voidBrentSingleOptimizer.minimize()This function estimates a function minimum within provided or computed bracket of values.voidConjugateGradientMultiOptimizer.minimize()This function estimates a function minimum.voidDerivativeBrentSingleOptimizer.minimize()This function estimates a function minimum within provided or computed bracket of values.voidDerivativeConjugateGradientMultiOptimizer.minimize()This function estimates a function minimum.voidGoldenSingleOptimizer.minimize()This function estimates a function minimum within provided or computed bracket of values.voidOptimizer.minimize()This function estimates a function minimum.voidPowellMultiOptimizer.minimize()This function estimates a function minimum.voidQuasiNewtonMultiOptimizer.minimize()This function estimates a function minimum.voidSimplexMultiOptimizer.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 NotReadyExceptionModifier and TypeMethodDescriptionLMedSPolynomialRobustEstimator.estimate()Estimates polynomial.LMSEPolynomialEstimator.estimate()Estimates a polynomial based on provided evaluations.MSACPolynomialRobustEstimator.estimate()Estimates polynomial.abstract PolynomialPolynomialEstimator.estimate()Estimates a polynomial based on provided evaluations.abstract PolynomialPolynomialRobustEstimator.estimate()Estimates polynomial.PROMedSPolynomialRobustEstimator.estimate()Estimates polynomial.PROSACPolynomialRobustEstimator.estimate()Estimates polynomial.RANSACPolynomialRobustEstimator.estimate()Estimates 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 NotReadyExceptionModifier and TypeMethodDescriptionLMedSRobustEstimator.estimate()Robustly estimates an instance of T.MSACRobustEstimator.estimate()Robustly estimates an instance of T.PROMedSRobustEstimator.estimate()Robustly estimates an instance of T.PROSACRobustEstimator.estimate()Robustly estimates an instance of T.RANSACRobustEstimator.estimate()Robustly estimates an instance of T.abstract TRobustEstimator.estimate()Robustly estimates an instance of T. -
Uses of NotReadyException in com.irurueta.numerical.roots
Methods in com.irurueta.numerical.roots that throw NotReadyExceptionModifier and TypeMethodDescriptionvoidBracketedSingleRootEstimator.computeBracket()Starting at zero, this method expands the range (i.e. bracket of values) until a zero crossing is found where a root is present or until the bracket becomes unacceptably large, where an exception will be raised.voidBracketedSingleRootEstimator.computeBracket(double point) Starting from provided point, this method expands the range (i.e.voidBracketedSingleRootEstimator.computeBracket(double minEvalPoint, double maxEvalPoint) Starting from provided minimum and maximum values, this method expands the range (i.e. bracket of values) until a zero crossing is found where a root is present or until the bracket becomes unacceptably large, where an exception will be raised.voidBisectionSingleRootEstimator.estimate()Estimates a single root of the provided single dimension function contained within a given bracket of values.voidBrentSingleRootEstimator.estimate()Estimates a local root for a given single dimension function being evaluated by provided listener.voidFalsePositionSingleRootEstimator.estimate()Estimates a single root of the provided single dimension function contained within a given bracket of values.voidFirstDegreePolynomialRootsEstimator.estimate()Estimates the root of provided polynomial.voidLaguerrePolynomialRootsEstimator.estimate()Estimates the roots of provided polynomial.voidNewtonRaphsonSingleRootEstimator.estimate()Estimates a local root for a given single dimension function being evaluated by provided listener.voidRidderSingleRootEstimator.estimate()Estimates a local root for a given single dimension function being evaluated by provided listener.voidRootEstimator.estimate()Estimates the root or roots for a given function.voidSafeNewtonRaphsonSingleRootEstimator.estimate()Estimates a local root for a given single dimension function being evaluated by provided listener.voidSecantSingleRootEstimator.estimate()Estimates a local root for a given single dimension function being evaluated by provided listener.voidSecondDegreePolynomialRootsEstimator.estimate()Estimates the roots of provided polynomial.voidThirdDegreePolynomialRootsEstimator.estimate()Estimates the roots of provided polynomial.booleanSecondDegreePolynomialRootsEstimator.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 rootbooleanThirdDegreePolynomialRootsEstimator.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).booleanThirdDegreePolynomialRootsEstimator.hasOneRealRootAndTwoComplexConjugateRoots()Returns boolean indicating whether the polynomial has one real root and two complex conjugate roots.booleanThirdDegreePolynomialRootsEstimator.hasThreeDistinctRealRoots()Returns boolean indicating whether the roots of the polynomial are three distinct and real roots or not.booleanSecondDegreePolynomialRootsEstimator.hasTwoComplexConjugateRoots()Returns boolean indicating whether the roots of the polynomial are two complex conjugate roots or not.booleanSecondDegreePolynomialRootsEstimator.hasTwoDistinctRealRoots()Returns boolean indicating whether the roots of the polynomial are two distinct and real roots or not.booleanFirstDegreePolynomialRootsEstimator.isFirstDegree()Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid first degree polynomial.booleanSecondDegreePolynomialRootsEstimator.isSecondDegree()Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid second degree polynomial.booleanThirdDegreePolynomialRootsEstimator.isThirdDegree()Returns boolean indicating whether polynomial parameters provided to this instance correspond to a valid third degree polynomial.