Uses of Class
org.hipparchus.linear.RealVector

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

Modifier	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

Modifier	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 uk-1.

Constructors in org.hipparchus.filtering.kalman.linear with parameters of type RealVector

Modifier	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

Modifier	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 ith 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

Modifier	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

Modifier	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

Modifier	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.
protected	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.