Shearer's inequality

In information theory, Shearer's inequality,^[1] named after James Shearer, states that if X₁, ..., X_d are random variables and S₁, ..., S_n are subsets of {1, 2, ..., d} such that every integer between 1 and d lies in at least r of these subsets, then

H[(X_{1},\dots ,X_{d})]\leq {\frac {1}{r}}\sum _{i=1}^{n}H[(X_{j})_{j\in S_{i}}]

where $(X_{j})_{j\in S_{i}}$ is the Cartesian product of random variables $X_{{j}}$ with indices j in $S_{i}$ (so the dimension of this vector is equal to the size of $S_{i}$ ).

References

↑ Chung, F.R.K.; Graham, R.L.; Frankl, P.; Shearer, J.B. (1986). "Some Intersection Theorems for Ordered Sets and Graphs". J. Comb. Theory A. 43: 23–37.

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[1] Chung, F.R.K.; Graham, R.L.; Frankl, P.; Shearer, J.B. (1986). "Some Intersection Theorems for Ordered Sets and Graphs". J. Comb. Theory A. 43: 23–37.