Uses of Class
org.apache.commons.math3.linear.RealVector

Packages that use RealVector

Package	Description
org.apache.commons.math3.analysis.interpolation	Univariate real functions interpolation algorithms.
org.apache.commons.math3.filter	Implementations of common discrete-time linear filters.
org.apache.commons.math3.fitting.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.
org.apache.commons.math3.linear	Linear algebra support.
org.apache.commons.math3.optim.linear	Optimization algorithms for linear constrained problems.
org.apache.commons.math3.optimization.linear	This package provides optimization algorithms for linear constrained problems.
org.apache.commons.math3.stat.regression	Statistical routines involving multivariate data.

Uses of RealVector in org.apache.commons.math3.analysis.interpolation

Fields in org.apache.commons.math3.analysis.interpolation declared as RealVector

Modifier and Type	Field	Description
private RealVector	MicrosphereInterpolatingFunction.MicrosphereSurfaceElement.normal	Normal vector characterizing a surface element.

Fields in org.apache.commons.math3.analysis.interpolation with type parameters of type RealVector

Modifier and Type	Field	Description
private java.util.Map.Entry<RealVector,java.lang.Double>	MicrosphereInterpolatingFunction.MicrosphereSurfaceElement.brightestSample	Brightest sample.
private java.util.Map<RealVector,java.lang.Double>	MicrosphereInterpolatingFunction.samples	Deprecated. Sample data.

Methods in org.apache.commons.math3.analysis.interpolation that return RealVector

Modifier and Type	Method	Description
(package private) RealVector	MicrosphereInterpolatingFunction.MicrosphereSurfaceElement.normal()	Return the normal vector.

Methods in org.apache.commons.math3.analysis.interpolation that return types with arguments of type RealVector

Modifier and Type	Method	Description
(package private) java.util.Map.Entry<RealVector,java.lang.Double>	MicrosphereInterpolatingFunction.MicrosphereSurfaceElement.sample()	Get the sample illuminating the element the most.

Methods in org.apache.commons.math3.analysis.interpolation with parameters of type RealVector

Modifier and Type	Method	Description
private double	MicrosphereInterpolatingFunction.cosAngle(RealVector v, RealVector w)	Deprecated. Compute the cosine of the angle between 2 vectors.

Method parameters in org.apache.commons.math3.analysis.interpolation with type arguments of type RealVector

Modifier and Type	Method	Description
(package private) void	MicrosphereInterpolatingFunction.MicrosphereSurfaceElement.store(double illuminationFromSample, java.util.Map.Entry<RealVector,java.lang.Double> sample)	Store the illumination and index of the brightest sample.

Uses of RealVector in org.apache.commons.math3.filter

Fields in org.apache.commons.math3.filter declared as RealVector

Modifier and Type	Field	Description
private RealVector	DefaultProcessModel.initialStateEstimateVector	The initial state estimation of the observed process.
private RealVector	KalmanFilter.stateEstimation	The internal state estimation vector, equivalent to x hat.

Methods in org.apache.commons.math3.filter that return RealVector

Modifier and Type	Method	Description
RealVector	DefaultProcessModel.getInitialStateEstimate()	Returns the initial state estimation vector.
RealVector	ProcessModel.getInitialStateEstimate()	Returns the initial state estimation vector.
RealVector	KalmanFilter.getStateEstimationVector()	Returns a copy of the current state estimation vector.

Methods in org.apache.commons.math3.filter with parameters of type RealVector

Modifier and Type	Method	Description
void	KalmanFilter.correct(RealVector z)	Correct the current state estimate with an actual measurement.
void	KalmanFilter.predict(RealVector u)	Predict the internal state estimation one time step ahead.

Constructors in org.apache.commons.math3.filter with parameters of type RealVector

Constructor	Description
DefaultProcessModel(RealMatrix stateTransition, RealMatrix control, RealMatrix processNoise, RealVector initialStateEstimate, RealMatrix initialErrorCovariance)	Create a new ProcessModel, taking double arrays as input parameters.

Uses of RealVector in org.apache.commons.math3.fitting.leastsquares

Fields in org.apache.commons.math3.fitting.leastsquares declared as RealVector

Modifier and Type	Field	Description
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation.point	Point of evaluation.
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.point	Point of evaluation.
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.residuals	Computed residuals.
private RealVector	LeastSquaresBuilder.start	initial guess
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.start	Initial guess.
private RealVector	LeastSquaresBuilder.target	observed values
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation.target	Target values for the model function at optimum.
private RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.target	Target values for the model function at optimum.

Methods in org.apache.commons.math3.fitting.leastsquares that return RealVector

Modifier and Type	Method	Description
RealVector	LeastSquaresFactory.LocalValueAndJacobianFunction.computeValue(double[] params)	Compute the value.
RealVector	ValueAndJacobianFunction.computeValue(double[] params)	Compute the value.
RealVector	DenseWeightedEvaluation.getPoint()	Get the abscissa (independent variables) of this evaluation.
RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation.getPoint()	Get the abscissa (independent variables) of this evaluation.
RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.getPoint()	Get the abscissa (independent variables) of this evaluation.
RealVector	LeastSquaresProblem.Evaluation.getPoint()	Get the abscissa (independent variables) of this evaluation.
RealVector	OptimumImpl.getPoint()	Get the abscissa (independent variables) of this evaluation.
RealVector	DenseWeightedEvaluation.getResiduals()	Get the weighted residuals.
RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation.getResiduals()	Get the weighted residuals.
RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.getResiduals()	Get the weighted residuals.
RealVector	LeastSquaresProblem.Evaluation.getResiduals()	Get the weighted residuals.
RealVector	OptimumImpl.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	OptimumImpl.getSigma(double covarianceSingularityThreshold)	Get an estimate of the standard deviation of the parameters.
RealVector	LeastSquaresAdapter.getStart()	Gets the initial guess.
RealVector	LeastSquaresFactory.LocalLeastSquaresProblem.getStart()	Gets the initial guess.
RealVector	LeastSquaresProblem.getStart()	Gets the initial guess.
protected abstract RealVector	GaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian, RealVector residuals)	Solve the linear least squares problem Jx=r.
RealVector	ParameterValidator.validate(RealVector params)	Validates the set of parameters.

Methods in org.apache.commons.math3.fitting.leastsquares that return types with arguments of type RealVector

Modifier and Type	Method	Description
private static Pair<RealMatrix,RealVector>	GaussNewtonOptimizer.computeNormalMatrix(RealMatrix jacobian, RealVector residuals)	Compute the normal matrix, JTJ.
Pair<RealVector,RealMatrix>	LeastSquaresFactory.LocalValueAndJacobianFunction.value(RealVector point)	Compute the function value and its Jacobian.
Pair<RealVector,RealMatrix>	MultivariateJacobianFunction.value(RealVector point)	Compute the function value and its Jacobian.

Methods in org.apache.commons.math3.fitting.leastsquares with parameters of type RealVector

Modifier and Type	Method	Description
private static Pair<RealMatrix,RealVector>	GaussNewtonOptimizer.computeNormalMatrix(RealMatrix jacobian, RealVector residuals)	Compute the normal matrix, JTJ.
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	LeastSquaresFactory.LocalLeastSquaresProblem.evaluate(RealVector point)	Evaluate the model at the specified point.
LeastSquaresProblem.Evaluation	LeastSquaresProblem.evaluate(RealVector point)	Evaluate the model at the specified point.
protected abstract RealVector	GaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian, RealVector residuals)	Solve the linear least squares problem Jx=r.
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>	LeastSquaresFactory.LocalValueAndJacobianFunction.value(RealVector point)	Compute the function value and its Jacobian.
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.

Constructors in org.apache.commons.math3.fitting.leastsquares with parameters of type RealVector

Constructor	Description
LazyUnweightedEvaluation(ValueAndJacobianFunction model, RealVector target, RealVector point)	Create an LeastSquaresProblem.Evaluation with no weights.
LocalLeastSquaresProblem(MultivariateJacobianFunction model, RealVector target, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)	Create a LeastSquaresProblem from the given data.
UnweightedEvaluation(RealVector values, RealMatrix jacobian, RealVector target, RealVector point)	Create an LeastSquaresProblem.Evaluation with no weights.

Uses of RealVector in org.apache.commons.math3.linear

Subclasses of RealVector in org.apache.commons.math3.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

Fields in org.apache.commons.math3.linear declared as RealVector

Modifier and Type	Field	Description
private RealVector	DefaultIterativeLinearSolverEvent.b	The right-hand side vector.
private RealVector	SymmLQ.State.b	Reference to the right-hand side vector.
private RealVector	SymmLQ.State.mb	The value of M * b.
private RealVector	DefaultIterativeLinearSolverEvent.r	The current estimate of the residual.
private RealVector	SymmLQ.State.r1	The value of beta[k] * M^(-1) * P' * v[k].
private RealVector	SymmLQ.State.r2	The value of beta[k+1] * M^(-1) * P' * v[k+1].
private RealVector	SymmLQ.State.wbar	The value of P' * wbar[k] or P' * (wbar[k] - s[1] * ...
private RealVector	DefaultIterativeLinearSolverEvent.x	The current estimate of the solution.
private RealVector	SymmLQ.State.xL	A reference to the vector to be updated with the solution.
private RealVector	SymmLQ.State.y	The value of beta[k+1] * P' * v[k+1].

Methods in org.apache.commons.math3.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.
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	EigenDecomposition.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 x.
RealVector	JacobiPreconditioner.operate(RealVector x)	Returns the result of multiplying this by the vector x.
abstract 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.
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	CholeskyDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	DecompositionSolver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	EigenDecomposition.Solver.solve(RealVector b)	Solves the linear equation A × X = B for symmetric 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	LUDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
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	QRDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	RRQRDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	SingularValueDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B in least square sense.
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.apache.commons.math3.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.
private static void	SymmLQ.State.checkSymmetry(RealLinearOperator l, RealVector x, RealVector y, RealVector z)	Performs a symmetry check on the specified linear operator, and throws an exception in case this check 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.
private static void	SymmLQ.State.daxpbypz(double a, RealVector x, double b, RealVector y, RealVector z)	A BLAS-like function, for the operation z ← a · x + b · y + z.
private static void	SymmLQ.State.daxpy(double a, RealVector x, RealVector y)	A clone of the BLAS DAXPY function, which carries out the operation y ← a · x + y.
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.
java.lang.String	RealVectorFormat.format(RealVector v)	This method calls RealVectorFormat.format(RealVector,StringBuffer,FieldPosition).
java.lang.StringBuffer	RealVectorFormat.format(RealVector vector, java.lang.StringBuffer toAppendTo, java.text.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 x.
RealVector	JacobiPreconditioner.operate(RealVector x)	Returns the result of multiplying this by the vector x.
abstract 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.
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.
(package private) void	SymmLQ.State.refineSolution(RealVector x)	Move to the CG point if it seems better.
static void	MatrixUtils.serializeRealVector(RealVector vector, java.io.ObjectOutputStream oos)	Serialize a RealVector.
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	CholeskyDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	DecompositionSolver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	EigenDecomposition.Solver.solve(RealVector b)	Solves the linear equation A × X = B for symmetric 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	LUDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
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	QRDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	RRQRDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B for matrices A.
RealVector	SingularValueDecomposition.Solver.solve(RealVector b)	Solve the linear equation A × X = B in least square sense.
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.
private static void	SymmLQ.State.throwNPDLOException(RealLinearOperator l, RealVector v)	Throws a new NonPositiveDefiniteOperatorException with appropriate context.
static RealVector	RealVector.unmodifiableRealVector(RealVector v)	Returns an unmodifiable view of the specified vector.

Constructors in org.apache.commons.math3.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(java.lang.Object source, int iterations, RealVector x, RealVector b, double rnorm)	Creates a new instance of this class.
DefaultIterativeLinearSolverEvent(java.lang.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.
State(RealLinearOperator a, RealLinearOperator m, RealVector b, boolean goodb, double shift, double delta, boolean check)	Creates and inits to k = 1 a new instance of this class.

Uses of RealVector in org.apache.commons.math3.optim.linear

Fields in org.apache.commons.math3.optim.linear declared as RealVector

Modifier and Type	Field	Description
private RealVector	LinearConstraint.coefficients	Coefficients of the constraint (left hand side).
private RealVector	LinearObjectiveFunction.coefficients	Coefficients of the linear equation (ci).

Methods in org.apache.commons.math3.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.apache.commons.math3.optim.linear with parameters of type RealVector

Modifier and Type	Method	Description
protected static double	SimplexTableau.getInvertedCoefficientSum(RealVector coefficients)	Get the -1 times the sum of all coefficients in the given array.
double	LinearObjectiveFunction.value(RealVector point)	Computes the value of the linear equation at the current point.

Constructors in org.apache.commons.math3.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)

Uses of RealVector in org.apache.commons.math3.optimization.linear

Fields in org.apache.commons.math3.optimization.linear declared as RealVector

Modifier and Type	Field	Description
private RealVector	LinearConstraint.coefficients	Deprecated. Coefficients of the constraint (left hand side).
private RealVector	LinearObjectiveFunction.coefficients	Deprecated. Coefficients of the constraint (ci).

Methods in org.apache.commons.math3.optimization.linear that return RealVector

Modifier and Type	Method	Description
RealVector	LinearConstraint.getCoefficients()	Deprecated. Get the coefficients of the constraint (left hand side).
RealVector	LinearObjectiveFunction.getCoefficients()	Deprecated. Get the coefficients of the linear equation being optimized.

Methods in org.apache.commons.math3.optimization.linear with parameters of type RealVector

Modifier and Type	Method	Description
protected static double	SimplexTableau.getInvertedCoefficientSum(RealVector coefficients)	Deprecated. Get the -1 times the sum of all coefficients in the given array.
double	LinearObjectiveFunction.getValue(RealVector point)	Deprecated. Compute the value of the linear equation at the current point

Constructors in org.apache.commons.math3.optimization.linear with parameters of type RealVector

Constructor	Description
LinearConstraint(RealVector lhsCoefficients, double lhsConstant, Relationship relationship, RealVector rhsCoefficients, double rhsConstant)	Deprecated. Build a constraint involving two linear equations.
LinearConstraint(RealVector coefficients, Relationship relationship, double value)	Deprecated. Build a constraint involving a single linear equation.
LinearObjectiveFunction(RealVector coefficients, double constantTerm)	Deprecated.

Uses of RealVector in org.apache.commons.math3.stat.regression

Fields in org.apache.commons.math3.stat.regression declared as RealVector

Modifier and Type	Field	Description
private RealVector	AbstractMultipleLinearRegression.yVector	Y sample data.

Methods in org.apache.commons.math3.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()