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  2. Numerical methods for linear least squares - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    An exception occurs in numerical smoothing and differentiation where an analytical expression is required. If the matrix X T X is well-conditioned and positive definite, implying that it has full rank, the normal equations can be solved directly by using the Cholesky decomposition R T R, where R is an upper triangular matrix, giving:

  3. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    The storage and computation overhead is such that the standard simplex method is a prohibitively expensive approach to solving large linear programming problems. In each simplex iteration, the only data required are the first row of the tableau, the (pivotal) column of the tableau corresponding to the entering variable and the right-hand-side.

  4. Constrained least squares - Wikipedia

    en.wikipedia.org/wiki/Constrained_least_squares

    In constrained least squares one solves a linear least squares problem with an additional constraint on the solution. [ 1 ] [ 2 ] This means, the unconstrained equation X β = y {\displaystyle \mathbf {X} {\boldsymbol {\beta }}=\mathbf {y} } must be fit as closely as possible (in the least squares sense) while ensuring that some other property ...

  5. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    However, some problems have distinct optimal solutions; for example, the problem of finding a feasible solution to a system of linear inequalities is a linear programming problem in which the objective function is the zero function (i.e., the constant function taking the value zero everywhere).

  6. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Mathematically, linear least squares is the problem of approximately solving an overdetermined system of linear equations A x = b, where b is not an element of the column space of the matrix A. The approximate solution is realized as an exact solution to A x = b', where b' is the projection of b onto the column space of A. The best ...

  7. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    The simplest method for solving a system of linear equations is to repeatedly eliminate variables. This method can be described as follows: In the first equation, solve for one of the variables in terms of the others. Substitute this expression into the remaining equations. This yields a system of equations with one fewer equation and unknown.

  8. Linear equation - Wikipedia

    en.wikipedia.org/wiki/Linear_equation

    Conversely, every line is the set of all solutions of a linear equation. The phrase "linear equation" takes its origin in this correspondence between lines and equations: a linear equation in two variables is an equation whose solutions form a line. If b ≠ 0, the line is the graph of the function of x that has been defined in the preceding ...

  9. Equation solving - Wikipedia

    en.wikipedia.org/wiki/Equation_solving

    An example of using Newton–Raphson method to solve numerically the equation f(x) = 0. In mathematics, to solve an equation is to find its solutions, which are the values (numbers, functions, sets, etc.) that fulfill the condition stated by the equation, consisting generally of two expressions related by an equals sign.

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