Linear algebra is the branch of mathematics concerning vector spaces and linear mappings between such spaces. Linear algebra is central to both pure and applied mathematics.

Provided below is a list of all the matrix operations and decompositions available in Mintoris Basic.

## d = MatDet(a())- Compute the matrix determinate. |

## c = MatCond(a())- Ratio of largest to smallest singular value. |

## r = MatRank(a())- Effective numerical rank, obtained from SVD. |

## n = MatNorm1(a())- Maximum column sum. |

## n = MatNorm2(a())- Maximum singular value. |

## n = MatNormF(a())- Square root of the sum of squares of all elements. |

## n = MatNormInf(a())- Maximum row sum. |

## t = MatTrace(a())- Sum of the diagonal elements. |

## c() = MatAdd(a(),b())- Add two matrices. C = A + B |

## c() = MatSub(a(),b())- Subtract two matrices. C = A - B |

## c() = MatMult(a(),b())- Linear algebraic matrix multiplication. C = A * B |

## c() = MatSolve(a(),b())- Solve A*X = B. Solution if A is square, least squares solution otherwise. |

## c() = MatUMinus(a())- Unary minus. C = -A |

## c() = MatRandom(rows, cols)- Generate matrix with random elements. |

## c() = MatInverse(a())- Inverse A if A is square, pseudoinverse otherwise. |

## c() = MatIdentity(rows, cols)- Returns an m-by-n matrix with ones on the diagonal and zeros elsewhere. |

## c() = MatTranspose(a())- Matrix transpose. |

## c() = MatSolveTranspose(a())- Solve X*A = B, which is also A'*X' = B' |