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Matrix programming—Mata

Environment

  • Interactive—type matrix expressions and see results
  • Development—full development environment for developing programs and commands
  • Automatically compiled code

General features and matrix operators

  • Support for real and complex values
  • Joining by rows or columns
  • Addition, subtraction, multiplication, and scalar division
  • Elementwise arithmetic
  • Transposition and reshaping
  • Kronecker and Hadamard products
  • Inner and outer products

Optimizer

  • Code the function, function and gradient, or function, gradient, and
  • Newton–Raphson, BFGS, DFP, BHHH, Nelder–Mead, and Gauss–Newton techniques
  • Versions for general problems and statistical problems like maximum likelihood
  • Covariance matrix based on Hessian, outer product of gradients, or robust/sandwich

Mathematical and matrix functions

  • LAPACK numerical analysis routines
  • Hundreds of mathematical, string, and matrix utility functions
  • Symmetric, nonsymmetric, and generalized inverses
  • Cholesky , LU , QR , and SVD solvers
  • Trigonometric and other transcendental functions
  • Gamma and factorial functions
  • Density and distribution functions
  • Polynomial evaluation , arithmetic, and calculus
  • Hilbert , Toeplitz , and Vandermonde matrices
  • Duplication , commutation , and elimination matrices
  • Random-number generation
  • Fast Fourier analysis
  • Cubic splines
  • Means , sums , minimums and maximums of matrices
  • Numerical first and second derivatives
Explore all of Mata’s functions.

Stata interface

  • Convert Stata datasets to matrices and vice versa
  • Virtual matrix views onto dataset
  • Access and set estimation-class and other macros
  • Manipulate dataset value labels

Compiled language

  • C/C++-like syntax
  • Structures
  • Pointers
  • Numeric and string types
  • Matrices as an intrinsic type, including row and column vectors and full matrices

Object-oriented programming

  • Inheritance
  • Virtual functions
  • Encapsulation of data structures and programs

Decompositions

  • Eigenvalues and eigenvectors
  • Cholesky
  • LU and LUD
  • QR
  • Schur
  • Hessenberg
  • Singular value
  • Permutation matrices

Data accumulation

  • Cross products
  • Cross products of deviations from means
  • Weighted and GLS-type cross products
  • Support for quad-precision cross products

Nonlinear system solver

  • Fixed-point and root-finding problems
  • Gauss–Seidel, Broyden–Powell, and Newton–Raphson methods

Other features

  • String scalars and matrices
  • File I/O , including buffered I/O
  • C-like syntax
  • Fast execution
  • Programmatic access to create word documents
  • Low-level cell-by-cell access to write results to and read data from Excel

Additional resource

Read the Introduction to Mata.

See New in Stata 13 for more about what was added in Stata 13.

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