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Note that the left function is closed convex, since f is proper closed convex and S is closed convex.
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If φ is an effectively computable (recursive) place selection, the compound test of first applying φ and then some recursive significance test is also a recursive significance test (since the class of recursive functions is closed under functional composition).
A class of probability functions is closed under conditioning if and only if any probability function that comes by conditioning from one in the class is itself in the class.
The set of Gaussian functions is closed under multiplication, i.e. the product of normal densities is also a normal density, with the mean and the variance of the product density given by μ = ∑ μ i σ i 2 ∑ 1 σ i 2 and σ 2 = 1 ∑ 1 σ i 2 respectively.
They proved also that the class of starlike functions and the class of close-to-convex functions are closed under convolution with the class.
From the result (2.2) we conclude that, if 6-convex functions are closed in uniform norms, then their third derivatives are also closed in weighted (L^{2} -norm.
Moreover, we conclude that if 6-convex functions are closed in uniform norm, then their third derivatives are closed in weighted (L^{2} -norm.
The distribution function is close to a tailward drifting Maxwellian.
A function is close-to-convex if there is a convex function (not necessarily normalized) such that.
It is easy to realize that the mapping function is close to the uniform distribution under increasing λ.
This function is close to 1 at high latitudes and decreases rapidly to 0 around (|lambda _q| le 45^circ).
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