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  2. 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 ...

  3. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    A matrix is in reduced row echelon form if it is in row echelon form, with the additional property that the first nonzero entry of each row is equal to and is the only nonzero entry of its column. The reduced row echelon form of a matrix is unique and does not depend on the sequence of elementary row operations used to obtain it.

  4. Row equivalence - Wikipedia

    en.wikipedia.org/wiki/Row_equivalence

    Elementary row operations do not affect the row space of a matrix. In particular, any two row equivalent matrices have the same row space. 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.

  5. Elementary matrix - Wikipedia

    en.wikipedia.org/wiki/Elementary_matrix

    A row can be replaced by the sum of that row and a multiple of another row. R i + k R j → R i , where i ≠ j {\displaystyle R_{i}+kR_{j}\rightarrow R_{i},{\mbox{where }}i\neq j} If E is an elementary matrix, as described below, to apply the elementary row operation to a matrix A , one multiplies A by the elementary matrix on the left, EA .

  6. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    Since row operations can affect linear dependence relations of the row vectors, such a basis is instead found indirectly using the fact that the column space of A T is equal to the row space of A. Using the example matrix A above, find A T and reduce it to row echelon form:

  7. Reduced form - Wikipedia

    en.wikipedia.org/wiki/Reduced_form

    The reduced form of the system is: = + = +, with vector of reduced form errors that each depends on all structural errors, where the matrix A must be nonsingular for the reduced form to exist and be unique. Again, each endogenous variable depends on potentially each exogenous variable.

  8. Small Latin squares and quasigroups - Wikipedia

    en.wikipedia.org/wiki/Small_Latin_squares_and...

    To reduce the problem somewhat, a Latin square can always be put into a standard form known as a reduced square. A reduced square has its top row elements written in some natural order for the symbol set (for example, integers in increasing order or letters in alphabetical order). The left column entries are put in the same order.

  9. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    Type 3: Add to one row a scalar multiple of another. Because these operations are reversible, the augmented matrix produced always represents a linear system that is equivalent to the original. There are several specific algorithms to row-reduce an augmented matrix, the simplest of which are Gaussian elimination and Gauss–Jordan elimination ...