Matrikssuppression

Matrikssuppression is a term used in Swedish mathematical and data-science literature to describe the process of suppressing or masking elements of a matrix. In practice it denotes actions that reduce a matrix to a smaller or simpler form, either by removing rows and columns to form a submatrix or by masking selected entries, for example by setting them to zero. The exact meaning can vary with context, but the core idea is to focus on a part of the data or to enforce sparsity.

The main forms of matrikssuppression are row and column suppression, where certain rows and/or columns are deleted to obtain a submatrix. A related form is element-wise masking, where a predefined mask determines which entries are kept and which are suppressed. Suppression can also be described in terms of blocks or principal submatrices, where a contiguous block of the matrix is retained while the rest is discarded or ignored.

A simple example: for a 3x3 matrix A, suppressing the second row and the second column yields the 2x2 submatrix consisting of the remaining entries in positions (1,1), (1,3), (3,1) and (3,3).

Applications of matrikssuppression appear in numerical linear algebra, where reduced systems are solved more efficiently, in statistics for submatrix analyses, and in data processing where masking is used to enforce sparsity or protect sensitive information. Related concepts include submatrices, principal minors, and matrix masking.

See also: submatrix, minor, masking, sparsity, principal submatrix.