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The method of false position provides an exact solution for linear functions, but more direct algebraic techniques have supplanted its use for these functions. However, in numerical analysis, double false position became a root-finding algorithm used in iterative numerical approximation techniques.
False position is similar to the secant method, except that, instead of retaining the last two points, it makes sure to keep one point on either side of the root. The false position method can be faster than the bisection method and will never diverge like the secant method.
For instance problem 19 asks one to calculate a quantity taken 1 + 1 / 2 times and added to 4 to make 10. [8] In other words, in modern mathematical notation we are asked to solve the linear equation: + = Solving these Aha problems involves a technique called method of false position. The technique is also called the method of false ...
This means that the false position method always converges; however, only with a linear order of convergence. Bracketing with a super-linear order of convergence as the secant method can be attained with improvements to the false position method (see Regula falsi § Improvements in regula falsi) such as the ITP method or the Illinois method.
Problem 19 asks one to calculate a quantity taken 1 and one-half times and added to 4 to make 10. [1] In modern mathematical notation, this linear equation is represented: + = Solving these Aha problems involves a technique called method of false position.
In numerical analysis, Ridders' method is a root-finding algorithm based on the false position method and the use of an exponential function to successively approximate a root of a continuous function (). The method is due to C. Ridders.
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The term "method of false position" has consistently been more common than "false position method" or "rule of false position" during the 20-21st centuries, according to Google ngrams. This article should be moved to Method of false position .