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The regula falsi method calculates the new solution estimate as the x-intercept of the line segment joining the endpoints of the function on the current bracketing interval. Essentially, the root is being approximated by replacing the actual function by a line segment on the bracketing interval and then using the classical double false position ...
The construction of the queried point c follows three steps: interpolation (similar to the regula falsi), truncation (adjusting the regula falsi similar to Regula falsi § Improvements in regula falsi) and then projection onto the minmax interval. The combination of these steps produces a simultaneously minmax optimal method with guarantees ...
The secant method does not require or guarantee that the root remains bracketed by sequential iterates, like the bisection method does, and hence it does not always converge. The false position method (or regula falsi) uses the same formula as the secant method.
Since the Han dynasty, as diophantine approximation being a prominent numerical method, the Chinese made substantial progress on polynomial evaluation. Algorithms like regula falsi and expressions like simple continued fractions are widely used and have been well-documented ever since.
But even if it were established that something meaning "False Positions" were being used to name that method, in 1591, but it was replaced by "Regula Falsi" (which is not a Latin translation of "false positioni") by 1691, then, with Regula Falsi becoming the widespread term, that wouldn't support False Positions as the more legitimate term.
Regula falsi is another method that fits the function to a degree-two polynomial, but it uses the first derivative at two points, rather than the first and second derivative at the same point. If the method is started close enough to a non-degenerate local minimum, then it has superlinear convergence of order φ ≈ 1.618 {\displaystyle \varphi ...
A root-finding algorithm is a numerical method or algorithm for finding a value x such that f(x) = 0, for a given function f. Here, x is a single real number . Root-finding algorithms are studied in numerical analysis .
For finding one root, Newton's method and other general iterative methods work generally well. For finding all the roots, arguably the most reliable method is the Francis QR algorithm computing the eigenvalues of the companion matrix corresponding to the polynomial, implemented as the standard method [1] in MATLAB.