# inequality

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Related to Strict inequality: strict interpretation, Much greater than
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• noun

## Antonyms for inequality

### lack of equality

#### Antonyms

References in periodicals archive ?
Thus we have [Z.sub.oi](x) [less than or equal to] [Z.sub.oi]([x.sup.*]) with strict inequality hold for at least one i, i [member of] {1, 2, ..., k} and which shows that [x.sup.*] is a pareto optimal solution of (2.10).
x [member of] (0, 2[pi]) with strict inequality on a positive measurable subset of (0,2[pi]), such that for a.e.
If [A.sub.I] [subset] [B.sub.I] then one of the above inequalities becomes strict inequality.
where [??] Suppose that strict inequality holds in (2.4).
* r'v > [sub.SSD]r'w if and only if [F.sup.(-2).sub.r'v](p) [greater than or equal to] [F.sup.(-2).sub.r'w](p) (p) for all p [member of] <0,1> with strict inequality for at least some p where second quantile functions [F.sup.(-2).sub.r'v] [F.sup.(-2).sub.r'w], are convex conjugate functions of [F.sup.(2).sub.r'v] and [F.sup.(2).sub.r'w], respectively, in the sense of Fenchel duality, see [18].
Thus with [m.sub.c] defined by (7), the inequalities [p.bar] < p (strict inequality) and X [less than or equal to] [m.sub.c] (non-strict inequality) are equivalent.
It appears, though, that strict inequality holds in all other cases.
Let us now see that in the three cases when [DELTA]([pi]) = 1, an additional strict inequality must be satisfied.
By adding the sides of this non-strict inequality to the corresponding sides of the preceding strict inequality, the strict inequality will remain valid.
FSD: The probability function f(X) is said to dominate the probability function g(X) by FSD if and only if [F.sub.1]([X.sub.n]) [less than or equal to] [G.sub.1]([X.sub.n]) for all n [less than or equal to] N with strict inequality for at least one n [less than or equal to] N, where
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