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That is, the Taylor series diverges at x if the distance between x and b is larger than the radius of convergence. The Taylor series can be used to calculate the value of an entire function at every point, if the value of the function, and of all of its derivatives, are known at a single point. Uses of the Taylor series for analytic functions ...
For iterative calculation of the above series, the following alternative formulation may be useful: = = (= (+)) = = + = because −(2k − 1)z 2 / k(2k + 1) expresses the multiplier to turn the k th term into the (k + 1) th term (considering z as the first term).
In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.
Now its Taylor series centered at z 0 converges on any disc B(z 0, r) with r < |z − z 0 |, where the same Taylor series converges at z ∈ C. Therefore, Taylor series of f centered at 0 converges on B(0, 1) and it does not converge for any z ∈ C with |z| > 1 due to the poles at i and −i.
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
That is, if we have a value for the cumulative distribution function, (), but do not know the x needed to obtain the (), we can use Newton's method to find x, and use the Taylor series expansion above to minimize the number of computations.
This formula can be obtained by Taylor series expansion: (+) = + ′ ()! ″ ()! () +. The complex-step derivative formula is only valid for calculating first-order derivatives. A generalization of the above for calculating derivatives of any order employs multicomplex numbers , resulting in multicomplex derivatives.
In 1706, John Machin used Gregory's series (the Taylor series for arctangent) and the identity = to calculate 100 digits of π (see § Machin-like formula below). [ 30 ] [ 31 ] In 1719, Thomas de Lagny used a similar identity to calculate 127 digits (of which 112 were correct).