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The diagram opposite shows a 3rd order solution to G A Sod's shock tube problem (Sod, 1978) using the above high resolution Kurganov and Tadmor Central Scheme (KT) but with parabolic reconstruction and van Albada limiter. This again illustrates the effectiveness of the MUSCL approach to solving the Euler equations.
s.t. – such that or so that or subject to. st – standard part function. STP – [it is] sufficient to prove. SU – special unitary group. sup – supremum of a set. [1] (Also written as lub, which stands for least upper bound.) supp – support of a function. swish – swish function, an activation function in data analysis.
f: finish: An italic f (Latin small letter f) written on a line representing a surface was an old way of indicating that the surface was to be machined rather than left in the as-cast or as-forged state. The "f" came from "finish" in the sense of "machine finish" as opposed to raw stock/casting/forging.
The method can be described as the FTCS (forward in time, centered in space) scheme with a numerical dissipation term of 1/2. One can view the Lax–Friedrichs method as an alternative to Godunov's scheme , where one avoids solving a Riemann problem at each cell interface, at the expense of adding artificial viscosity.
Fisher's k-statistics and Tukey's polykays are examples of homogeneous polynomial U-statistics (Fisher, 1929; Tukey, 1950). For a simple random sample φ of size n taken from a population of size N, the U-statistic has the property that the average over sample values ƒ n (xφ) is exactly equal to the population value ƒ N (x). [clarification ...
We have the canonical duality pairing between a distribution T on U and a test function (), which is denoted using angle brackets by {′ () (,) , := () One interprets this notation as the distribution T acting on the test function f {\displaystyle f} to give a scalar, or symmetrically as the test function f {\displaystyle f} acting on the ...
In statistics, the uncertainty coefficient, also called proficiency, entropy coefficient or Theil's U, is a measure of nominal association. It was first introduced by Henri Theil [ citation needed ] and is based on the concept of information entropy .