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In numerical analysis, Aitken's delta-squared process or Aitken extrapolation is a series acceleration method used for accelerating the rate of convergence of a sequence. It is named after Alexander Aitken, who introduced this method in 1926. [1]
Two classical techniques for series acceleration are Euler's transformation of series [1] and Kummer's transformation of series. [2] A variety of much more rapidly convergent and special-case tools have been developed in the 20th century, including Richardson extrapolation, introduced by Lewis Fry Richardson in the early 20th century but also known and used by Katahiro Takebe in 1722; the ...
A sequence of discretized approximations () of some continuous-domain function that converges to this target, together with a corresponding sequence of discretization scale parameters () that converge to 0, is said to have asymptotic order of convergence and asymptotic rate of convergence if
Given a function :, consider the problem of finding a fixed point of , which is a solution to the equation () =.A classical approach to the problem is to employ a fixed-point iteration scheme; [2] that is, given an initial guess for the solution, to compute the sequence + = until some convergence criterion is met.
For given x, Padé approximants can be computed by Wynn's epsilon algorithm [2] and also other sequence transformations [3] from the partial sums = + + + + of the Taylor series of f, i.e., we have = ()!. f can also be a formal power series, and, hence, Padé approximants can also be applied to the summation of divergent series.
Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function.Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time.
The formula for an integration by parts is () ′ = [() ()] ′ (). Beside the boundary conditions , we notice that the first integral contains two multiplied functions, one which is integrated in the final integral ( g ′ {\displaystyle g'} becomes g {\displaystyle g} ) and one which is differentiated ( f {\displaystyle f} becomes f ...
For data expressed as a discrete sequence, ... Then the definition of the autocorrelation function between times and is [1]: p.388 [2] ...