Uses of Class
com.irurueta.algebra.WrongSizeException

Packages that use WrongSizeException

Package	Description
com.irurueta.algebra	This package contains classes related to algebra, such as Matrix class to contains matrices data and simple operations or Complex to handle computations with Complex numbers.
com.irurueta.statistics

Uses of WrongSizeException in com.irurueta.algebra

Methods in com.irurueta.algebra that throw WrongSizeException

Modifier and Type	Method	Description
void	Matrix.add(Matrix other)	Adds provided matrix to this instance.
void	Matrix.add(Matrix other, Matrix result)	Adds another matrix to this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.addAndReturnNew(Matrix other)	Adds provided matrix to this instance and returns the result as a new matrix instance.
static Matrix	Matrix.createWithGaussianRandomValues(int rows, int columns, double mean, double standardDeviation)	Creates new matrix instance using provided size and containing gaussian/normal distributed random values with provided median and standard deviation.
static Matrix	Matrix.createWithGaussianRandomValues(int rows, int columns, double mean, double standardDeviation, Random random)	Creates new matrix instance using provided size and containing gaussian/normal distributed random values with provided median and standard deviation and using provided random generator
static Matrix	Matrix.createWithUniformRandomValues(int rows, int columns, double minValue, double maxValue)	Creates new matrix instance using provided size and containing uniformly distributed random values with provided range.
static Matrix	Matrix.createWithUniformRandomValues(int rows, int columns, double minValue, double maxValue, Random random)	Creates new matrix instance using provided size and containing uniformly distributed random values with provided range and using provided random generator
static double[]	Utils.crossProduct(double[] v1, double[] v2)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static void	Utils.crossProduct(double[] v1, double[] v2, double[] result)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static void	Utils.crossProduct(double[] v1, double[] v2, double[] result, Matrix jacobian1, Matrix jacobian2)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static double[]	Utils.crossProduct(double[] v1, double[] v2, Matrix jacobian1, Matrix jacobian2)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static Matrix	Utils.crossProduct(double[] v, Matrix m)	Computes the cross product of one vector of length 3 and N vectors of length 3.
static void	Utils.crossProduct(double[] v, Matrix m, Matrix result)	Computes the cross product of one vector of length 3 and N vectors of length 3.
static double	Utils.det(Matrix m)	Computes determinant of provided matrix.
double	LUDecomposer.determinant()	Returns determinant of provided input matrix using LU decomposition as means to obtain it.
static double	Utils.dotProduct(Matrix firstOperand, Matrix secondOperand)	Computes the dot product of provided matrices, as the sum of the product of the elements on both matrices, assuming that both represent column vectors.
static double	Utils.dotProduct(Matrix firstOperand, Matrix secondOperand, Matrix jacobianFirst, Matrix jacobianSecond)	Computes the dot product of provided matrices, as the sum of the product of the elements on both matrices, assuming that both represent column vectors.
void	Matrix.elementByElementProduct(Matrix other)	Computes element by element product (i.e.
void	Matrix.elementByElementProduct(Matrix other, Matrix result)	Computes element by element product (i.e.
Matrix	Matrix.elementByElementProductAndReturnNew(Matrix other)	Computes element by element product (i.e.
void	Matrix.fromArray(double[] array)	Copies elements of array into this instance using column order.
void	Matrix.fromArray(double[] array, boolean isColumnOrder)	Copies elements of array into this instance using provided order.
double	NormComputer.getNorm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
Matrix	EconomyQRDecomposer.getQ()	Return the economy-sized orthogonal factor matrix.
void	EconomyQRDecomposer.getQ(Matrix q)	Computes the economy-sized orthogonal factor matrix and stores it into provided matrix.
void	Matrix.getSubmatrixAsArray(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, boolean isColumnOrder, double[] array)	Retrieves a sub-matrix of current matrix instance as an array of values using provided column order and storing the result in provided array.
void	Matrix.getSubmatrixAsArray(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, double[] array)	Retrieves a sub-matrix of current matrix instance as an array of values using column order and storing the result in provided array.
void	SingularValueDecomposer.getW(Matrix m)	Copies diagonal matrix into provided instance containing all singular values on its diagonal after Singular Value matrix decomposition, which consists on decomposing a matrix using the following expression: A = U * S * V'.
static Matrix	Matrix.identity(int rows, int columns)	Creates and returns a new matrix instance having all the elements on the diagonal equal to one and the remaining ones equal to zero.
private void	Matrix.internalResize(int rows, int columns)	Method used internally to remove matrix contents and resizing it.
private static void	Utils.internalSkewMatrix(Matrix m, Matrix result, boolean columnwise)	Internal method to compute skew matrix
static void	GaussJordanElimination.inverse(Matrix a)	Computes inverse of matrix "a".
static Matrix	Utils.inverse(double[] array)	Computes array pseudo-inverse considering it as a column matrix.
static void	Utils.inverse(double[] array, Matrix result)	Computes array pseudo-inverse considering it as a column matrix and stores the result in provided result matrix.
static Matrix	Utils.inverse(Matrix m)	Computes matrix inverse if provided matrix is squared, or pseudo-inverse otherwise.
static void	Utils.inverse(Matrix m, Matrix result)	Computes matrix inverse if provided matrix is squared, or pseudo-inverse otherwise and stores the result in provided result matrix.
boolean	EconomyQRDecomposer.isFullRank()	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	EconomyQRDecomposer.isFullRank(double roundingError)	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	LUDecomposer.isSingular()	Return boolean indicating whether provided input matrix is singular or not after computing LU decomposition.
boolean	LUDecomposer.isSingular(double roundingError)	Return boolean indicating whether provided input matrix is singular or not after computing LU decomposition.
void	Matrix.multiply(Matrix other)	Multiplies this matrix with provided matrix.
void	Matrix.multiply(Matrix other, Matrix result)	Multiplies another matrix to this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.multiplyAndReturnNew(Matrix other)	Multiplies this matrix with provided matrix and returns the result as a new instance.
static double	FrobeniusNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static double	InfinityNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static double	OneNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static void	GaussJordanElimination.process(Matrix a, double[] b)	Computes Gauss-Jordan elimination by attempting to solve linear system of equations a * x = b.
static void	GaussJordanElimination.process(Matrix a, Matrix b)	Computes Gauss-Jordan elimination by attempting to solve linear system of equations a * x = b.
void	Matrix.reset(int rows, int columns, double initValue)	Resets current instance by removing its contents, resizing it to provided size and setting all its elements to provided value.
void	Matrix.resize(int rows, int columns)	Resizes current instance by removing its contents and resizing it to provided size.
static Matrix	Utils.skewMatrix(double[] array)	Computes the skew-symmetric matrix of provided vector of length 3.
static void	Utils.skewMatrix(double[] array, Matrix result)	Computes the skew-symmetric matrix of provided vector of length 3 and stores the result in provided matrix.
static void	Utils.skewMatrix(double[] array, Matrix result, Matrix jacobian)	Computes the skew-symmetric matrix of provided vector of length 3 and stores the result in provided matrix.
static Matrix	Utils.skewMatrix(Matrix m)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
static void	Utils.skewMatrix(Matrix m, Matrix result)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
static void	Utils.skewMatrix(Matrix m, Matrix result, Matrix jacobian)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
Matrix	CholeskyDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
void	CholeskyDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
Matrix	EconomyQRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	EconomyQRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
void	EconomyQRDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
void	EconomyQRDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	LUDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	LUDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
void	LUDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
void	LUDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
void	QRDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
void	QRDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
double[]	SingularValueDecomposer.solve(double[] b)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
double[]	SingularValueDecomposer.solve(double[] b, double singularValueThreshold)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(double[] b, double[] result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(double[] b, double singularValueThreshold, double[] result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
Matrix	SingularValueDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
Matrix	SingularValueDecomposer.solve(Matrix b, double singularValueThreshold)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(Matrix b, double singularValueThreshold, Matrix result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
static Matrix	Utils.solve(Matrix m, Matrix b)	Solves a linear system of equations of the form: m * x = b.
static void	Utils.solve(Matrix m, Matrix b, Matrix result)	Solves a linear system of equations of the form: m * x = b.
void	Matrix.subtract(Matrix other)	Subtracts provided matrix from this instance.
void	Matrix.subtract(Matrix other, Matrix result)	Subtracts another matrix from this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.subtractAndReturnNew(Matrix other)	Subtracts provided matrix from this instance and returns the result as a new matrix instance.
void	Matrix.symmetrize()	Symmetrizes this instance and updates it with computed value.
void	Matrix.symmetrize(Matrix result)	Symmetrizes this instance and stores the result into provided instance.
Matrix	Matrix.symmetrizeAndReturnNew()	Symmetrizes this instance and returns the result as a new matrix instance.
void	Matrix.toArray(double[] result)	Copies the contents of the matrix to an array of values using column order.
void	Matrix.toArray(double[] result, boolean isColumnOrder)	Copies the contents of the matrix to an array of values using provided order to pick elements.

Constructors in com.irurueta.algebra that throw WrongSizeException

Modifier	Constructor	Description
	Matrix(int rows, int columns)	Constructor of this class.

Uses of WrongSizeException in com.irurueta.statistics

Methods in com.irurueta.statistics that throw WrongSizeException

Modifier and Type	Method	Description
static MultivariateNormalDist	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, double[] mean, Matrix covariance)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
static void	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, double[] mean, Matrix covariance, MultivariateNormalDist result)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
static MultivariateNormalDist	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, MultivariateNormalDist dist)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
static void	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, MultivariateNormalDist dist, MultivariateNormalDist result)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
MultivariateNormalDist	MultivariateNormalDist.propagateThisDistribution(MultivariateNormalDist.JacobianEvaluator evaluator)	Evaluates the Jacobian and a multivariate function at the mean point of this distribution and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
void	MultivariateNormalDist.propagateThisDistribution(MultivariateNormalDist.JacobianEvaluator evaluator, MultivariateNormalDist result)	Evaluates the Jacobian and a multivariate function at the mean point of this distribution and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
final void	MultivariateGaussianRandomizer.setMeanAndCovariance(double[] mean, Matrix covariance)	Sets mean and covariance to generate multivariate Gaussian random values.

Constructors in com.irurueta.statistics that throw WrongSizeException

Modifier	Constructor	Description
	MultivariateGaussianRandomizer(double[] mean, Matrix covariance)	Constructor.
	MultivariateGaussianRandomizer(Random internalRandom, double[] mean, Matrix covariance)	Constructor.