method of approximation
81Nelder–Mead method — Nelder–Mead simplex search over the Rosenbrock banana function (above) and Himmelblau s function (below) See simplex algorithm for Dantzig s algorithm for the problem of linear opti …
82Boundary element method — The boundary element method is a numerical computational method of solving linear partial differential equations which have been formulated as integral equations (i.e. in boundary integral form). It can be applied in many areas of engineering and …
83Müller's method — is a root finding algorithm, a numerical method for solving equations of the form f(x) = 0. It is first presented by D. E. Müller in 1956. Müller s method is based on the secant method, which constructs at every iteration a line through two… …
84Quasi-Monte Carlo method — In numerical analysis, a quasi Monte Carlo method is a method for the computation of an integral (or some other problem) that is based on low discrepancy sequences. This is in contrast to a regular Monte Carlo method, which is based on sequences… …
85Cutting-plane method — In mathematical optimization, the cutting plane method is an umbrella term for optimization methods which iteratively refine a feasible set or objective function by means of linear inequalities, termed cuts. Such procedures are popularly used to… …
86Finite-difference time-domain method — Finite difference time domain (FDTD) is a popular computational electrodynamics modeling technique. It is considered easy to understand and easy to implement in software. Since it is a time domain method, solutions can cover a wide frequency… …
87Delta method — In statistics, the delta method is a method for deriving an approximate probability distribution for a function of an asymptotically normal statistical estimator from knowledge of the limiting variance of that estimator. More broadly, the delta… …
88Euler method — In mathematics and computational science, the Euler method, named after Leonhard Euler, is a first order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It is the most basic kind of explicit… …
89Quasi-Newton method — In optimization, quasi Newton methods (also known as variable metric methods) are well known algorithms for finding local maxima and minima of functions. Quasi Newton methods are based on Newton s method to find the stationary point of a function …
90Information bottleneck method — The information bottleneck method is a technique introduced by Tishby et al [1] for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability… …
