/** * Gets the square-root of the weight matrix. * * @return the square-root of the weight matrix. */ public RealMatrix getWeightSquareRoot() { return weightMatrixSqrt.copy(); }
/** * Gets the square-root of the weight matrix. * * @return the square-root of the weight matrix. * @since 3.1 */ public RealMatrix getWeightSquareRoot() { return weightMatrixSqrt.copy(); }
/** * Gets the initial guess. * * @return the initial guess. */ public RealMatrix getWeight() { return weightMatrix.copy(); } }
/** * Gets the initial guess. * * @return the initial guess. */ public RealMatrix getWeight() { return weightMatrix.copy(); } }
/** * Gets the covariance matrix. * * @return the covariance matrix. */ public RealMatrix getCovariances() { return covarianceMatrix.copy(); }
/** * Gets the weight matrix of the observations. * * @return the weight matrix. * @since 3.1 */ public RealMatrix getWeight() { return weightMatrix.copy(); } /**
/** * Returns a copy of the current error covariance matrix. * * @return the error covariance matrix */ public RealMatrix getErrorCovarianceMatrix() { return errorCovariance.copy(); }
/** * Gets the weight matrix of the observations. * * @return the weight matrix. */ public RealMatrix getWeight() { return weightMatrix.copy(); } /**
/** * @param weight Weight matrix. * @throws NonSquareMatrixException if the argument is not * a square matrix. */ public Weight(RealMatrix weight) { if (weight.getColumnDimension() != weight.getRowDimension()) { throw new NonSquareMatrixException(weight.getColumnDimension(), weight.getRowDimension()); } weightMatrix = weight.copy(); }
/** * @param weight Weight matrix. * @throws NonSquareMatrixException if the argument is not * a square matrix. */ public Weight(RealMatrix weight) { if (weight.getColumnDimension() != weight.getRowDimension()) { throw new NonSquareMatrixException(weight.getColumnDimension(), weight.getRowDimension()); } weightMatrix = weight.copy(); }
/** Build a simple converter for correlated residuals with the specific weights. * <p> * The scalar objective function value is computed as: * <pre> * objective = y<sup>T</sup>y with y = scale×(observation-objective) * </pre> * </p> * <p> * The array computed by the objective function, the observations array and the * the scaling matrix must have consistent sizes or a {@link DimensionMismatchException} * will be triggered while computing the scalar objective. * </p> * @param function vectorial residuals function to wrap * @param observations observations to be compared to objective function to compute residuals * @param scale scaling matrix * @throws DimensionMismatchException if the observations vector and the scale * matrix dimensions do not match (objective function dimension is checked only when * the {@link #value(double[])} method is called) */ public LeastSquaresConverter(final MultivariateVectorFunction function, final double[] observations, final RealMatrix scale) { if (observations.length != scale.getColumnDimension()) { throw new DimensionMismatchException(observations.length, scale.getColumnDimension()); } this.function = function; this.observations = observations.clone(); this.weights = null; this.scale = scale.copy(); }
this.observations = observations.clone(); this.weights = null; this.scale = scale.copy();
transformed = matrix.copy();
/** * Gets the square-root of the weight matrix. * * @return the square-root of the weight matrix. */ public RealMatrix getWeightSquareRoot() { return weightMatrixSqrt.copy(); }
/** * Returns a copy of the current error covariance matrix. * * @return the error covariance matrix */ public RealMatrix getErrorCovarianceMatrix() { return errorCovariance.copy(); }
errorCovariance = processNoise.copy(); } else { errorCovariance = processModel.getInitialErrorCovariance();
/** * Gets the square-root of the weight matrix. * * @return the square-root of the weight matrix. */ public RealMatrix getWeightSquareRoot() { return weightMatrixSqrt.copy(); }
/** * Gets the initial guess. * * @return the initial guess. */ public RealMatrix getWeight() { return weightMatrix.copy(); } }
/** * Returns a copy of the current error covariance matrix. * * @return the error covariance matrix */ public RealMatrix getErrorCovarianceMatrix() { return errorCovariance.copy(); }
/** * Gets the weight matrix of the observations. * * @return the weight matrix. * @since 3.1 */ public RealMatrix getWeight() { return weightMatrix.copy(); } /**