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  2. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    A system of linear equations is said to be in row echelon form if its augmented matrix is in row echelon form. Similarly, a system of linear equations is said to be in reduced row echelon form or in canonical form if its augmented matrix is in reduced row echelon form. The canonical form may be viewed as an explicit solution of the linear system.

  3. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    Using row operations to convert a matrix into reduced row echelon form is sometimes called Gauss–Jordan elimination. In this case, the term Gaussian elimination refers to the process until it has reached its upper triangular, or (unreduced) row echelon form. For computational reasons, when solving systems of linear equations, it is sometimes ...

  4. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    Cramer's rule is a closed-form expression, in terms of determinants, of the solution of a system of n linear equations in n unknowns. Cramer's rule is useful for reasoning about the solution, but, except for n = 2 or 3 , it is rarely used for computing a solution, since Gaussian elimination is a faster algorithm.

  5. Rouché–Capelli theorem - Wikipedia

    en.wikipedia.org/wiki/Rouché–Capelli_theorem

    The theorem can be read almost directly on the reduced row echelon form as follows. The rank of a matrix is the number of nonzero rows in its reduced row echelon form. If the ranks of the coefficient matrix and the augmented matrix are different, then the last non zero row has the form [ 0 … 0 ∣ 1 ] , {\displaystyle [0\ldots 0\mid 1 ...

  6. Reduced form - Wikipedia

    en.wikipedia.org/wiki/Reduced_form

    In econometrics, the equations of a structural form model are estimated in their theoretically given form, while an alternative approach to estimation is to first solve the theoretical equations for the endogenous variables to obtain reduced form equations, and then to estimate the reduced form equations.

  7. Row equivalence - Wikipedia

    en.wikipedia.org/wiki/Row_equivalence

    Any matrix can be reduced by elementary row operations to a matrix in reduced row echelon form. Two matrices in reduced row echelon form have the same row space if and only if they are equal. This line of reasoning also proves that every matrix is row equivalent to a unique matrix with reduced row echelon form.

  8. Howell normal form - Wikipedia

    en.wikipedia.org/wiki/Howell_normal_form

    Note that and are two distinct matrices in the row echelon form, which would mean that their span is the same if they're treated as matrices over some field. Moreover, they're in the Hermite normal form , meaning that their row span is also the same if they're considered over Z {\displaystyle \mathbb {Z} } , the ring of integers .

  9. Hermite normal form - Wikipedia

    en.wikipedia.org/wiki/Hermite_normal_form

    In linear algebra, the Hermite normal form is an analogue of reduced echelon form for matrices over the integers.Just as reduced echelon form can be used to solve problems about the solution to the linear system = where , the Hermite normal form can solve problems about the solution to the linear system = where this time is restricted to have integer coordinates only.

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