Uses of Class org.hipparchus.linear.RealVector (Hipparchus 4.0.2 API)

Packages that use RealVector
Package	Description
org.hipparchus.filtering.kalman	Kalman filter.
org.hipparchus.filtering.kalman.extended	Kalman filter implementation for non-linear processes.
org.hipparchus.filtering.kalman.linear	Kalman filter implementation for linear processes.
org.hipparchus.filtering.kalman.unscented	Unscented Kalman filter implementation.
org.hipparchus.linear	Linear algebra support.
org.hipparchus.optim.linear	Optimization algorithms for linear constrained problems.
org.hipparchus.optim.nonlinear.vector.constrained	This package provides algorithms that minimize the residuals between observations and model values.
org.hipparchus.optim.nonlinear.vector.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.
org.hipparchus.stat.regression	Statistical routines involving multivariate data.
org.hipparchus.util	Convenience routines and common data structures used throughout the Hipparchus library.

Uses of RealVector in org.hipparchus.filtering.kalman

Methods in org.hipparchus.filtering.kalman that return RealVector
Modifier and Type	Method	Description
`RealVector`	ProcessEstimate.`getState()`	Get the state vector.
`RealVector`	Measurement.`getValue()`	Get the measurement vector.

Methods in org.hipparchus.filtering.kalman with parameters of type RealVector
Modifier and Type	Method	Description
`protected void`	AbstractKalmanFilter.`correct(T measurement, RealMatrix stm, RealVector innovation, RealMatrix h, RealMatrix s)`	Perform correction step.
`protected void`	AbstractKalmanFilter.`predict(double time, RealVector predictedState, RealMatrix stm, RealMatrix noise)`	Perform prediction step.

Constructors in org.hipparchus.filtering.kalman with parameters of type RealVector
Constructor	Description
`ProcessEstimate(double time, RealVector state, RealMatrix covariance)`	Simple constructor.
`ProcessEstimate(double time, RealVector state, RealMatrix covariance, RealMatrix stateTransitionMatrix, RealMatrix measurementJacobian, RealMatrix innovationCovariance, RealMatrix kalmanGain)`	Simple constructor.

Uses of RealVector in org.hipparchus.filtering.kalman.extended

Methods in org.hipparchus.filtering.kalman.extended that return RealVector
Modifier and Type	Method	Description
`RealVector`	NonLinearEvolution.`getCurrentState()`	Get current state.
`RealVector`	NonLinearProcess.`getInnovation(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix)`	Get the innovation brought by a measurement.

Methods in org.hipparchus.filtering.kalman.extended with parameters of type RealVector
Modifier and Type	Method	Description
`NonLinearEvolution`	NonLinearProcess.`getEvolution(double previousTime, RealVector previousState, T measurement)`	Get the state evolution between two times.

Constructors in org.hipparchus.filtering.kalman.extended with parameters of type RealVector
Constructor	Description
`NonLinearEvolution(double currentTime, RealVector currentState, RealMatrix stateTransitionMatrix, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian)`	Simple constructor.

Uses of RealVector in org.hipparchus.filtering.kalman.linear

Methods in org.hipparchus.filtering.kalman.linear that return RealVector
Modifier and Type	Method	Description
`RealVector`	LinearEvolution.`getCommand()`	Get the command u_k-1.

Constructors in org.hipparchus.filtering.kalman.linear with parameters of type RealVector
Constructor	Description
`LinearEvolution(RealMatrix stateTransitionMatrix, RealMatrix controlMatrix, RealVector command, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian)`	Simple constructor.

Uses of RealVector in org.hipparchus.filtering.kalman.unscented

Methods in org.hipparchus.filtering.kalman.unscented that return RealVector
Modifier and Type	Method	Description
`RealVector[]`	UnscentedEvolution.`getCurrentStates()`	Get current states.
`RealVector`	UnscentedProcess.`getInnovation(T measurement, RealVector predictedMeasurement, RealVector predictedState, RealMatrix innovationCovarianceMatrix)`	Get the innovation brought by a measurement.
`RealVector[]`	UnscentedProcess.`getPredictedMeasurements(RealVector[] predictedSigmaPoints, T measurement)`	Get the state evolution between two times.

Methods in org.hipparchus.filtering.kalman.unscented with parameters of type RealVector
Modifier and Type	Method	Description
`UnscentedEvolution`	UnscentedProcess.`getEvolution(double previousTime, RealVector[] sigmaPoints, T measurement)`	Get the state evolution between two times.
`RealVector`	UnscentedProcess.`getInnovation(T measurement, RealVector predictedMeasurement, RealVector predictedState, RealMatrix innovationCovarianceMatrix)`	Get the innovation brought by a measurement.
`RealVector[]`	UnscentedProcess.`getPredictedMeasurements(RealVector[] predictedSigmaPoints, T measurement)`	Get the state evolution between two times.
`RealMatrix`	UnscentedProcess.`getProcessNoiseMatrix(double previousTime, RealVector predictedState, T measurement)`	Get the process noise covariance corresponding to the state evolution between two times.

Constructors in org.hipparchus.filtering.kalman.unscented with parameters of type RealVector
Constructor	Description
`UnscentedEvolution(double currentTime, RealVector[] currentStates)`	Constructor.

Uses of RealVector in org.hipparchus.linear

Subclasses of RealVector in org.hipparchus.linear
Modifier and Type	Class	Description
`class`	`ArrayRealVector`	This class implements the `RealVector` interface with a double array.
`class`	`OpenMapRealVector`	This class implements the `RealVector` interface with a `OpenIntToDoubleHashMap` backing store.
`class`	`SparseRealVector`	Marker class for RealVectors that require sparse backing storage

Methods in org.hipparchus.linear that return RealVector
Modifier and Type	Method	Description
`RealVector`	OpenMapRealVector.`add(RealVector v)`	Compute the sum of this vector and `v`.
`RealVector`	RealVector.`add(RealVector v)`	Compute the sum of this vector and `v`.
`RealVector`	ArrayRealVector.`append(double in)`	Construct a new vector by appending a double to this vector.
`RealVector`	ArrayRealVector.`append(RealVector v)`	Construct a new vector by appending a vector to this vector.
`abstract RealVector`	RealVector.`append(double d)`	Construct a new vector by appending a double to this vector.
`abstract RealVector`	RealVector.`append(RealVector v)`	Construct a new vector by appending a vector to this vector.
`RealVector`	RealVector.`combine(double a, double b, RealVector y)`	Returns a new vector representing `a * this + b * y`, the linear combination of `this` and `y`.
`RealVector`	RealVector.`combineToSelf(double a, double b, RealVector y)`	Updates `this` with the linear combination of `this` and `y`.
`abstract RealVector`	RealVector.`copy()`	Returns a (deep) copy of this vector.
`static RealVector`	MatrixUtils.`createRealVector(double[] data)`	Creates a `RealVector` using the data from the input array.
`static RealVector`	MatrixUtils.`createRealVector(int dimension)`	Creates a `RealVector` with specified dimensions.
`abstract RealVector`	RealVector.`ebeDivide(RealVector v)`	Element-by-element division.
`abstract RealVector`	RealVector.`ebeMultiply(RealVector v)`	Element-by-element multiplication.
`RealVector`	AbstractRealMatrix.`getColumnVector(int column)`	Get the entries at the given column index as a vector.
`RealVector`	BlockRealMatrix.`getColumnVector(int column)`	Get the entries at the given column index as a vector.
`RealVector`	RealMatrix.`getColumnVector(int column)`	Get the entries at the given column index as a vector.
`RealVector`	EigenDecompositionSymmetric.`getEigenvector(int i)`	Gets a copy of the i^th eigenvector of the original matrix.
`RealVector`	DefaultIterativeLinearSolverEvent.`getResidual()`	Returns the residual.
`RealVector`	IterativeLinearSolverEvent.`getResidual()`	Returns the residual.
`RealVector`	DefaultIterativeLinearSolverEvent.`getRightHandSideVector()`	Returns the current right-hand side of the linear system to be solved.
`abstract RealVector`	IterativeLinearSolverEvent.`getRightHandSideVector()`	Returns the current right-hand side of the linear system to be solved.
`RealVector`	AbstractRealMatrix.`getRowVector(int row)`	Returns the entries in row number `row` as a vector.
`RealVector`	BlockRealMatrix.`getRowVector(int row)`	Returns the entries in row number `row` as a vector.
`RealVector`	RealMatrix.`getRowVector(int row)`	Returns the entries in row number `row` as a vector.
`RealVector`	DefaultIterativeLinearSolverEvent.`getSolution()`	Returns the current estimate of the solution to the linear system to be solved.
`abstract RealVector`	IterativeLinearSolverEvent.`getSolution()`	Returns the current estimate of the solution to the linear system to be solved.
`RealVector`	ArrayRealVector.`getSubVector(int index, int n)`	Get a subvector from consecutive elements.
`abstract RealVector`	RealVector.`getSubVector(int index, int n)`	Get a subvector from consecutive elements.
`RealVector`	RealVector.`map(UnivariateFunction function)`	Acts as if implemented as:
`RealVector`	RealVector.`mapAdd(double d)`	Add a value to each entry.
`RealVector`	ArrayRealVector.`mapAddToSelf(double d)`	Add a value to each entry.
`RealVector`	RealVector.`mapAddToSelf(double d)`	Add a value to each entry.
`RealVector`	RealVector.`mapDivide(double d)`	Divide each entry by the argument.
`RealVector`	ArrayRealVector.`mapDivideToSelf(double d)`	Divide each entry by the argument.
`RealVector`	RealVector.`mapDivideToSelf(double d)`	Divide each entry by the argument.
`RealVector`	RealVector.`mapMultiply(double d)`	Multiply each entry by the argument.
`RealVector`	ArrayRealVector.`mapMultiplyToSelf(double d)`	Multiply each entry.
`RealVector`	RealVector.`mapMultiplyToSelf(double d)`	Multiply each entry.
`RealVector`	RealVector.`mapSubtract(double d)`	Subtract a value from each entry.
`RealVector`	ArrayRealVector.`mapSubtractToSelf(double d)`	Subtract a value from each entry.
`RealVector`	RealVector.`mapSubtractToSelf(double d)`	Subtract a value from each entry.
`RealVector`	RealVector.`mapToSelf(UnivariateFunction function)`	Acts as if it is implemented as:
`RealVector`	AbstractRealMatrix.`operate(RealVector v)`	Returns the result of multiplying this by the vector `v`.
`RealVector`	JacobiPreconditioner.`operate(RealVector x)`	Returns the result of multiplying `this` by the vector `x`.
`RealVector`	RealLinearOperator.`operate(RealVector x)`	Returns the result of multiplying `this` by the vector `x`.
`RealVector`	RealMatrix.`operate(RealVector v)`	Returns the result of multiplying this by the vector `v`.
`default RealVector`	RealLinearOperator.`operateTranspose(RealVector x)`	Returns the result of multiplying the transpose of `this` operator by the vector `x` (optional operation).
`RealVector`	AbstractRealMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	DiagonalMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	RealMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	RealVector.`projection(RealVector v)`	Find the orthogonal projection of this vector onto another vector.
`RealVector`	DecompositionSolver.`solve(RealVector b)`	Solve the linear equation A × X = B for matrices A.
`RealVector`	IterativeLinearSolver.`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, RealVector x0)`	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`	PreconditionedIterativeLinearSolver.`solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)`	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`	PreconditionedIterativeLinearSolver.`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, 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`	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`	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`	IterativeLinearSolver.`solveInPlace(RealLinearOperator a, 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`	PreconditionedIterativeLinearSolver.`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, 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`	SymmLQ.`solveInPlace(RealLinearOperator a, RealVector b, RealVector x)`	Returns an estimate of the solution to the linear system A · x = b.
`RealVector`	OpenMapRealVector.`subtract(RealVector v)`	Subtract `v` from this vector.
`RealVector`	RealVector.`subtract(RealVector v)`	Subtract `v` from this vector.
`RealVector`	RealVector.`unitVector()`	Creates a unit vector pointing in the direction of this vector.
`static RealVector`	RealVector.`unmodifiableRealVector(RealVector v)`	Returns an unmodifiable view of the specified vector.

Methods in org.hipparchus.linear that return types with arguments of type RealVector
Modifier and Type	Method	Description
`static List<RealVector>`	MatrixUtils.`orthonormalize(List<RealVector> independent, double threshold, DependentVectorsHandler handler)`	Orthonormalize a list of vectors.

Methods in org.hipparchus.linear with parameters of type RealVector
Modifier and Type	Method	Description
`ArrayRealVector`	ArrayRealVector.`add(RealVector v)`	Compute the sum of this vector and `v`.
`RealVector`	OpenMapRealVector.`add(RealVector v)`	Compute the sum of this vector and `v`.
`RealVector`	RealVector.`add(RealVector v)`	Compute the sum of this vector and `v`.
`RealVector`	ArrayRealVector.`append(RealVector v)`	Construct a new vector by appending a vector to this vector.
`OpenMapRealVector`	OpenMapRealVector.`append(RealVector v)`	Construct a new vector by appending a vector to this vector.
`abstract RealVector`	RealVector.`append(RealVector v)`	Construct a new vector by appending a vector to this vector.
`protected static void`	IterativeLinearSolver.`checkParameters(RealLinearOperator a, RealVector b, RealVector x0)`	Performs all dimension checks on the parameters of `solve` and `solveInPlace`, and throws an exception if one of the checks fails.
`protected static void`	PreconditionedIterativeLinearSolver.`checkParameters(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)`	Performs all dimension checks on the parameters of `solve` and `solveInPlace`, and throws an exception if one of the checks fails.
`protected void`	ArrayRealVector.`checkVectorDimensions(RealVector v)`	Check if instance and specified vectors have the same dimension.
`protected void`	RealVector.`checkVectorDimensions(RealVector v)`	Check if instance and specified vectors have the same dimension.
`ArrayRealVector`	ArrayRealVector.`combine(double a, double b, RealVector y)`	Returns a new vector representing `a * this + b * y`, the linear combination of `this` and `y`.
`RealVector`	RealVector.`combine(double a, double b, RealVector y)`	Returns a new vector representing `a * this + b * y`, the linear combination of `this` and `y`.
`ArrayRealVector`	ArrayRealVector.`combineToSelf(double a, double b, RealVector y)`	Updates `this` with the linear combination of `this` and `y`.
`RealVector`	RealVector.`combineToSelf(double a, double b, RealVector y)`	Updates `this` with the linear combination of `this` and `y`.
`double`	RealVector.`cosine(RealVector v)`	Computes the cosine of the angle between this vector and the argument.
`double`	ArrayRealVector.`dotProduct(RealVector v)`	Compute the dot product of this vector with `v`.
`double`	RealVector.`dotProduct(RealVector v)`	Compute the dot product of this vector with `v`.
`ArrayRealVector`	ArrayRealVector.`ebeDivide(RealVector v)`	Element-by-element division.
`OpenMapRealVector`	OpenMapRealVector.`ebeDivide(RealVector v)`	Element-by-element division.
`abstract RealVector`	RealVector.`ebeDivide(RealVector v)`	Element-by-element division.
`ArrayRealVector`	ArrayRealVector.`ebeMultiply(RealVector v)`	Element-by-element multiplication.
`OpenMapRealVector`	OpenMapRealVector.`ebeMultiply(RealVector v)`	Element-by-element multiplication.
`abstract RealVector`	RealVector.`ebeMultiply(RealVector v)`	Element-by-element multiplication.
`String`	RealVectorFormat.`format(RealVector v)`	This method calls `RealVectorFormat.format(RealVector,StringBuffer,FieldPosition)`.
`StringBuffer`	RealVectorFormat.`format(RealVector vector, StringBuffer toAppendTo, FieldPosition pos)`	Formats a `RealVector` object to produce a string.
`double`	ArrayRealVector.`getDistance(RealVector v)`	Distance between two vectors.
`double`	OpenMapRealVector.`getDistance(RealVector v)`	Distance between two vectors.
`double`	RealVector.`getDistance(RealVector v)`	Distance between two vectors.
`double`	ArrayRealVector.`getL1Distance(RealVector v)`	Distance between two vectors.
`double`	OpenMapRealVector.`getL1Distance(RealVector v)`	Distance between two vectors.
`double`	RealVector.`getL1Distance(RealVector v)`	Distance between two vectors.
`double`	ArrayRealVector.`getLInfDistance(RealVector v)`	Distance between two vectors.
`double`	OpenMapRealVector.`getLInfDistance(RealVector v)`	Distance between two vectors.
`double`	RealVector.`getLInfDistance(RealVector v)`	Distance between two vectors.
`RealVector`	AbstractRealMatrix.`operate(RealVector v)`	Returns the result of multiplying this by the vector `v`.
`RealVector`	JacobiPreconditioner.`operate(RealVector x)`	Returns the result of multiplying `this` by the vector `x`.
`RealVector`	RealLinearOperator.`operate(RealVector x)`	Returns the result of multiplying `this` by the vector `x`.
`RealVector`	RealMatrix.`operate(RealVector v)`	Returns the result of multiplying this by the vector `v`.
`default RealVector`	RealLinearOperator.`operateTranspose(RealVector x)`	Returns the result of multiplying the transpose of `this` operator by the vector `x` (optional operation).
`RealMatrix`	ArrayRealVector.`outerProduct(RealVector v)`	Compute the outer product.
`RealMatrix`	RealVector.`outerProduct(RealVector v)`	Compute the outer product.
`RealVector`	AbstractRealMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	DiagonalMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	RealMatrix.`preMultiply(RealVector v)`	Returns the (row) vector result of premultiplying this by the vector `v`.
`RealVector`	RealVector.`projection(RealVector v)`	Find the orthogonal projection of this vector onto another vector.
`void`	AbstractRealMatrix.`setColumnVector(int column, RealVector vector)`	Sets the specified `column` of `this` matrix to the entries of the specified `vector`.
`void`	BlockRealMatrix.`setColumnVector(int column, RealVector vector)`	Sets the specified `column` of `this` matrix to the entries of the specified `vector`.
`void`	RealMatrix.`setColumnVector(int column, RealVector vector)`	Sets the specified `column` of `this` matrix to the entries of the specified `vector`.
`void`	AbstractRealMatrix.`setRowVector(int row, RealVector vector)`	Sets the specified `row` of `this` matrix to the entries of the specified `vector`.
`void`	BlockRealMatrix.`setRowVector(int row, RealVector vector)`	Sets the specified `row` of `this` matrix to the entries of the specified `vector`.
`void`	RealMatrix.`setRowVector(int row, RealVector vector)`	Sets the specified `row` of `this` matrix to the entries of the specified `vector`.
`void`	ArrayRealVector.`setSubVector(int index, RealVector v)`	Set a sequence of consecutive elements.
`void`	OpenMapRealVector.`setSubVector(int index, RealVector v)`	Set a sequence of consecutive elements.
`abstract void`	RealVector.`setSubVector(int index, RealVector v)`	Set a sequence of consecutive elements.
`RealVector`	DecompositionSolver.`solve(RealVector b)`	Solve the linear equation A × X = B for matrices A.
`RealVector`	IterativeLinearSolver.`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, RealVector x0)`	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`	PreconditionedIterativeLinearSolver.`solve(RealLinearOperator a, RealLinearOperator m, RealVector b, RealVector x0)`	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`	PreconditionedIterativeLinearSolver.`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, 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`	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`	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`	IterativeLinearSolver.`solveInPlace(RealLinearOperator a, 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`	PreconditionedIterativeLinearSolver.`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, 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`	SymmLQ.`solveInPlace(RealLinearOperator a, RealVector b, RealVector x)`	Returns an estimate of the solution to the linear system A · x = b.
`static void`	MatrixUtils.`solveLowerTriangularSystem(RealMatrix rm, RealVector b)`	Solve a system of composed of a Lower Triangular Matrix `RealMatrix`.
`static void`	MatrixUtils.`solveUpperTriangularSystem(RealMatrix rm, RealVector b)`	Solver a system composed of an Upper Triangular Matrix `RealMatrix`.
`ArrayRealVector`	ArrayRealVector.`subtract(RealVector v)`	Subtract `v` from this vector.
`RealVector`	OpenMapRealVector.`subtract(RealVector v)`	Subtract `v` from this vector.
`RealVector`	RealVector.`subtract(RealVector v)`	Subtract `v` from this vector.
`static RealVector`	RealVector.`unmodifiableRealVector(RealVector v)`	Returns an unmodifiable view of the specified vector.

Method parameters in org.hipparchus.linear with type arguments of type RealVector
Modifier and Type	Method	Description
`abstract int`	DependentVectorsHandler.`manageDependent(int index, List<RealVector> basis)`	Manage a dependent vector.
`static List<RealVector>`	MatrixUtils.`orthonormalize(List<RealVector> independent, double threshold, DependentVectorsHandler handler)`	Orthonormalize a list of vectors.

Constructors in org.hipparchus.linear with parameters of type RealVector
Constructor	Description
`ArrayRealVector(ArrayRealVector v1, RealVector v2)`	Construct a vector by appending one vector to another vector.
`ArrayRealVector(RealVector v)`	Construct a vector from another vector, using a deep copy.
`ArrayRealVector(RealVector v1, ArrayRealVector v2)`	Construct a vector by appending one vector to another vector.
`DefaultIterativeLinearSolverEvent(Object source, int iterations, RealVector x, RealVector b, double rnorm)`	Creates a new instance of this class.
`DefaultIterativeLinearSolverEvent(Object source, int iterations, RealVector x, RealVector b, RealVector r, double rnorm)`	Creates a new instance of this class.
`OpenMapRealVector(RealVector v)`	Generic copy constructor.

Uses of RealVector in org.hipparchus.optim.linear

Methods in org.hipparchus.optim.linear that return RealVector
Modifier and Type	Method	Description
`RealVector`	LinearConstraint.`getCoefficients()`	Gets the coefficients of the constraint (left hand side).
`RealVector`	LinearObjectiveFunction.`getCoefficients()`	Gets the coefficients of the linear equation being optimized.

Methods in org.hipparchus.optim.linear with parameters of type RealVector
Modifier and Type	Method	Description
`double`	LinearObjectiveFunction.`value(RealVector point)`	Computes the value of the linear equation at the current point.

Constructors in org.hipparchus.optim.linear with parameters of type RealVector
Constructor	Description
`LinearConstraint(RealVector lhsCoefficients, double lhsConstant, Relationship relationship, RealVector rhsCoefficients, double rhsConstant)`	Build a constraint involving two linear equations.
`LinearConstraint(RealVector coefficients, Relationship relationship, double value)`	Build a constraint involving a single linear equation.
`LinearObjectiveFunction(RealVector coefficients, double constantTerm)`	Simple constructor.

Uses of RealVector in org.hipparchus.optim.nonlinear.vector.constrained

Methods in org.hipparchus.optim.nonlinear.vector.constrained that return RealVector
Modifier and Type	Method	Description
`RealVector`	LagrangeSolution.`getLambda()`	Returns Lambda Multiplier
`RealVector`	BoundedConstraint.`getLowerBound()`	Get Lower Bound for `value(x)`.
`RealVector`	Constraint.`getLowerBound()`	Get Lower Bound for `value(x)`.
`RealVector`	QuadraticFunction.`getQ()`	Get vector of weights for linear terms.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`getScaledLUb(RealVector lb1)`	Get scaled upper bound
`RealVector`	ADMMQPModifiedRuizEquilibrium.`getScaledQ()`	Get scaled vector of weights for linear terms.
`RealVector`	BoundedConstraint.`getUpperBound()`	Get Upper Bound for `value(x)`.
`RealVector`	Constraint.`getUpperBound()`	Get Upper Bound for `value(x)`.
`RealVector`	ADMMQPSolution.`getV()`	Returns V tilde auxiliary Variable
`RealVector`	LagrangeSolution.`getX()`	Returns X solution
`RealVector`	ADMMQPSolution.`getZ()`	Returns Z auxiliary Variable
`RealVector`	QuadraticFunction.`gradient(RealVector x)`	Returns the gradient of this function at (x)
`RealVector`	TwiceDifferentiableFunction.`gradient(double[] x)`	Returns the gradient of this function at (x)
`abstract RealVector`	TwiceDifferentiableFunction.`gradient(RealVector x)`	Returns the gradient of this function at (x)
`protected RealVector`	AbstractSQPOptimizer.`lagrangianGradX(RealVector currentGrad, RealMatrix jacobConstraint, RealVector x, RealVector y)`	Compute Lagrangian gradient for variable X
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleX(RealVector x)`	Unscale solution vector.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleY(RealVector y)`	Unscale Y vector.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleZ(RealVector z)`	Unscale Z vector.
`RealVector`	LinearBoundedConstraint.`value(RealVector x)`	Returns the value of this function at (x)
`RealVector`	LinearEqualityConstraint.`value(RealVector x)`
`RealVector`	LinearInequalityConstraint.`value(RealVector x)`
`RealVector`	VectorDifferentiableFunction.`value(RealVector x)`	Returns the value of this function at (x)

Methods in org.hipparchus.optim.nonlinear.vector.constrained with parameters of type RealVector
Modifier and Type	Method	Description
`RealVector`	ADMMQPModifiedRuizEquilibrium.`getScaledLUb(RealVector lb1)`	Get scaled upper bound
`RealVector`	QuadraticFunction.`gradient(RealVector x)`	Returns the gradient of this function at (x)
`abstract RealVector`	TwiceDifferentiableFunction.`gradient(RealVector x)`	Returns the gradient of this function at (x)
`RealMatrix`	QuadraticFunction.`hessian(RealVector x)`	The Hessian of this function at (x)
`abstract RealMatrix`	TwiceDifferentiableFunction.`hessian(RealVector x)`	The Hessian of this function at (x)
`void`	ADMMQPKKT.`initialize(RealMatrix newH, RealMatrix newA, RealVector newQ, int me, RealVector newLb, RealVector newUb, double rho, double newSigma, double newAlpha)`	Initialize problem
`ADMMQPSolution`	ADMMQPKKT.`iterate(RealVector... previousSol)`	Iterate Karush–Kuhn–Tucker equation from given list of Vector
`T`	KarushKuhnTuckerSolver.`iterate(RealVector... b)`	Iterate Karush–Kuhn–Tucker equation from given list of Vector
`RealMatrix`	LinearBoundedConstraint.`jacobian(RealVector x)`	Returns the gradient of this function at (x)
`RealMatrix`	LinearEqualityConstraint.`jacobian(RealVector x)`
`RealMatrix`	LinearInequalityConstraint.`jacobian(RealVector x)`
`RealMatrix`	VectorDifferentiableFunction.`jacobian(RealVector x)`	Returns the gradient of this function at (x)
`protected RealVector`	AbstractSQPOptimizer.`lagrangianGradX(RealVector currentGrad, RealMatrix jacobConstraint, RealVector x, RealVector y)`	Compute Lagrangian gradient for variable X
`double`	ADMMQPConvergenceChecker.`maxDual(RealVector x, RealVector y)`	Compute dual vectors max.
`double`	ADMMQPConvergenceChecker.`maxPrimal(RealVector x, RealVector z)`	Compute primal vectors max.
`double`	BoundedConstraint.`overshoot(RealVector y)`	Check how much a point overshoots the constraint.
`double`	Constraint.`overshoot(RealVector y)`	Check how much a point overshoots the constraint.
`double`	ADMMQPConvergenceChecker.`residualDual(RealVector x, RealVector y)`	Compute dual residual.
`double`	ADMMQPConvergenceChecker.`residualPrime(RealVector x, RealVector z)`	Compute primal residual.
`ADMMQPSolution`	ADMMQPKKT.`solve(RealVector b1, RealVector b2)`	Solve Karush–Kuhn–Tucker equation from given right hand value.
`T`	KarushKuhnTuckerSolver.`solve(RealVector b1, RealVector b2)`	Solve Karush–Kuhn–Tucker equation from given right hand value.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleX(RealVector x)`	Unscale solution vector.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleY(RealVector y)`	Unscale Y vector.
`RealVector`	ADMMQPModifiedRuizEquilibrium.`unscaleZ(RealVector z)`	Unscale Z vector.
`RealVector`	LinearBoundedConstraint.`value(RealVector x)`	Returns the value of this function at (x)
`RealVector`	LinearEqualityConstraint.`value(RealVector x)`
`RealVector`	LinearInequalityConstraint.`value(RealVector x)`
`double`	QuadraticFunction.`value(RealVector x)`	Returns the value of this function at (x)
`abstract double`	TwiceDifferentiableFunction.`value(RealVector x)`	Returns the value of this function at (x)
`RealVector`	VectorDifferentiableFunction.`value(RealVector x)`	Returns the value of this function at (x)

Constructors in org.hipparchus.optim.nonlinear.vector.constrained with parameters of type RealVector
Constructor	Description
`ADMMQPModifiedRuizEquilibrium(RealMatrix H, RealMatrix A, RealVector q)`	Simple constructor
`ADMMQPSolution(RealVector x, RealVector v)`	Simple constructor.
`ADMMQPSolution(RealVector x, RealVector lambda, Double value)`	Simple constructor.
`ADMMQPSolution(RealVector x, RealVector v, RealVector y, RealVector z)`	Simple constructor.
`ADMMQPSolution(RealVector x, RealVector v, RealVector y, RealVector z, double value)`	Simple constructor.
`BoundedConstraint(RealVector lower, RealVector upper)`	Simple constructor.
`EqualityConstraint(RealVector value)`	Simple constructor.
`InequalityConstraint(RealVector lower)`	Simple constructor.
`LagrangeSolution(RealVector x, RealVector lambda, double value)`	Simple constructor.
`LinearBoundedConstraint(RealMatrix a, RealVector lower, RealVector upper)`	Construct a set of linear inequality constraints from Ax < B
`LinearEqualityConstraint(RealMatrix a, RealVector b)`	Construct a set of linear equality constraints ax = b.
`LinearInequalityConstraint(RealMatrix a, RealVector b)`	Construct a set of linear inequality constraints from \( A x \gt B\).
`QuadraticFunction(RealMatrix p, RealVector q, double d)`	Construct quadratic function \(\frac{1}{2}x^T P X + Q^T x + d\).

Uses of RealVector in org.hipparchus.optim.nonlinear.vector.leastsquares

Methods in org.hipparchus.optim.nonlinear.vector.leastsquares that return RealVector
Modifier and Type	Method	Description
`RealVector`	ValueAndJacobianFunction.`computeValue(double[] params)`	Compute the value.
`RealVector`	LeastSquaresProblem.Evaluation.`getPoint()`	Get the abscissa (independent variables) of this evaluation.
`RealVector`	LeastSquaresProblem.Evaluation.`getResiduals()`	Get the weighted residuals.
`RealVector`	AbstractEvaluation.`getSigma(double covarianceSingularityThreshold)`	Get an estimate of the standard deviation of the parameters.
`RealVector`	LeastSquaresProblem.Evaluation.`getSigma(double covarianceSingularityThreshold)`	Get an estimate of the standard deviation of the parameters.
`RealVector`	LeastSquaresAdapter.`getStart()`	Gets the initial guess.
`RealVector`	LeastSquaresProblem.`getStart()`	Gets the initial guess.
`RealVector`	ParameterValidator.`validate(RealVector params)`	Validates the set of parameters.

Methods in org.hipparchus.optim.nonlinear.vector.leastsquares that return types with arguments of type RealVector
Modifier and Type	Method	Description
`Pair<RealVector,RealMatrix>`	MultivariateJacobianFunction.`value(RealVector point)`	Compute the function value and its Jacobian.

Methods in org.hipparchus.optim.nonlinear.vector.leastsquares with parameters of type RealVector
Modifier and Type	Method	Description
`static LeastSquaresProblem`	LeastSquaresFactory.`create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)`	Create a `LeastSquaresProblem` from the given elements.
`static LeastSquaresProblem`	LeastSquaresFactory.`create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)`	Create a `LeastSquaresProblem` from the given elements.
`static LeastSquaresProblem`	LeastSquaresFactory.`create(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)`	Create a `LeastSquaresProblem` from the given elements.
`LeastSquaresProblem.Evaluation`	LeastSquaresAdapter.`evaluate(RealVector point)`	Evaluate the model at the specified point.
`LeastSquaresProblem.Evaluation`	LeastSquaresProblem.`evaluate(RealVector point)`	Evaluate the model at the specified point.
`LeastSquaresBuilder`	LeastSquaresBuilder.`start(RealVector newStart)`	Configure the initial guess.
`LeastSquaresBuilder`	LeastSquaresBuilder.`target(RealVector newTarget)`	Configure the observed data.
`RealVector`	ParameterValidator.`validate(RealVector params)`	Validates the set of parameters.
`Pair<RealVector,RealMatrix>`	MultivariateJacobianFunction.`value(RealVector point)`	Compute the function value and its Jacobian.
`static LeastSquaresProblem`	LeastSquaresFactory.`weightDiagonal(LeastSquaresProblem problem, RealVector weights)`	Apply a diagonal weight matrix to the `LeastSquaresProblem`.
`SequentialGaussNewtonOptimizer`	SequentialGaussNewtonOptimizer.`withAPrioriData(RealVector aPrioriState, RealMatrix aPrioriCovariance)`	Configure from a priori state and covariance.
`SequentialGaussNewtonOptimizer`	SequentialGaussNewtonOptimizer.`withAPrioriData(RealVector aPrioriState, RealMatrix aPrioriCovariance, double relativeSymmetryThreshold, double absolutePositivityThreshold)`	Configure from a priori state and covariance.

Uses of RealVector in org.hipparchus.stat.regression

Methods in org.hipparchus.stat.regression that return RealVector
Modifier and Type	Method	Description
`protected abstract RealVector`	AbstractMultipleLinearRegression.`calculateBeta()`	Calculates the beta of multiple linear regression in matrix notation.
`protected RealVector`	GLSMultipleLinearRegression.`calculateBeta()`	Calculates beta by GLS.
`protected RealVector`	OLSMultipleLinearRegression.`calculateBeta()`	Calculates the regression coefficients using OLS.
`protected RealVector`	AbstractMultipleLinearRegression.`calculateResiduals()`	Calculates the residuals of multiple linear regression in matrix notation.
`protected RealVector`	AbstractMultipleLinearRegression.`getY()`	Get the Y sample data.

Uses of RealVector in org.hipparchus.util

Methods in org.hipparchus.util that return RealVector
Modifier and Type	Method	Description
`default RealVector`	UnscentedTransformProvider.`getUnscentedMeanState(RealVector[] sigmaPoints)`	Computes a weighted mean state from a given set of sigma points.
`RealVector`	JulierUnscentedTransform.`getWc()`	Get the covariance weights.
`RealVector`	MerweUnscentedTransform.`getWc()`	Get the covariance weights.
`RealVector`	UnscentedTransformProvider.`getWc()`	Get the covariance weights.
`RealVector`	JulierUnscentedTransform.`getWm()`	Get the mean weights.
`RealVector`	MerweUnscentedTransform.`getWm()`	Get the mean weights.
`RealVector`	UnscentedTransformProvider.`getWm()`	Get the mean weights.
`RealVector[]`	AbstractUnscentedTransform.`unscentedTransform(RealVector state, RealMatrix covariance)`	Perform the unscented transform from a state and its covariance.
`RealVector[]`	UnscentedTransformProvider.`unscentedTransform(RealVector state, RealMatrix covariance)`	Perform the unscented transform from a state and its covariance.

Methods in org.hipparchus.util that return types with arguments of type RealVector
Modifier and Type	Method	Description
`default Pair<RealVector,RealMatrix>`	UnscentedTransformProvider.`inverseUnscentedTransform(RealVector[] sigmaPoints)`	Perform the inverse unscented transform from an array of sigma points.

Methods in org.hipparchus.util with parameters of type RealVector
Modifier and Type	Method	Description
`default RealMatrix`	UnscentedTransformProvider.`getUnscentedCovariance(RealVector[] sigmaPoints, RealVector meanState)`	Computes the unscented covariance matrix from a weighted mean state and a set of sigma points.
`default RealVector`	UnscentedTransformProvider.`getUnscentedMeanState(RealVector[] sigmaPoints)`	Computes a weighted mean state from a given set of sigma points.
`default Pair<RealVector,RealMatrix>`	UnscentedTransformProvider.`inverseUnscentedTransform(RealVector[] sigmaPoints)`	Perform the inverse unscented transform from an array of sigma points.
`RealVector[]`	AbstractUnscentedTransform.`unscentedTransform(RealVector state, RealMatrix covariance)`	Perform the unscented transform from a state and its covariance.
`RealVector[]`	UnscentedTransformProvider.`unscentedTransform(RealVector state, RealMatrix covariance)`	Perform the unscented transform from a state and its covariance.

Uses of Classorg.hipparchus.linear.RealVector

Uses of RealVector in org.hipparchus.filtering.kalman

Uses of RealVector in org.hipparchus.filtering.kalman.extended

Uses of RealVector in org.hipparchus.filtering.kalman.linear

Uses of RealVector in org.hipparchus.filtering.kalman.unscented

Uses of RealVector in org.hipparchus.linear

Uses of RealVector in org.hipparchus.optim.linear

Uses of RealVector in org.hipparchus.optim.nonlinear.vector.constrained

Uses of RealVector in org.hipparchus.optim.nonlinear.vector.leastsquares

Uses of RealVector in org.hipparchus.stat.regression

Uses of RealVector in org.hipparchus.util

Uses of Class
org.hipparchus.linear.RealVector