Alphabeta Math
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Nonnegativity of finite relative entropy with a positive reference

Statement

Let p=(pi)i=1m and q=(qi)i=1m be probability vectors with qi>0 for every i. Then D(p∥q)≥0, with equality if and only if p=q.

Facts & Assumptions

Given: Probability vectors p,q on [m], with qi>0 for every i.

[F1]

Finite distributions, entropy, divergence, and stochastic matrices: D(p∥q)=∑i:pi>0piln⁡(pi/qi) when no positive coordinate of p is paired with a zero coordinate of q.

[F2]

Information units and logarithm-base convention: ln⁡ denotes the natural logarithm log⁡ of the library's natural-logarithm definition.

[F5]

The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t: The natural logarithm is differentiable for positive inputs and has derivative 1/t.

[A1]

qi>0 for all i, so the finite relative entropy in [F1] is defined by its displayed finite sum.

Proof

1.1F2F3F4F5F6givenchoosealgebra

If t=1, then ln⁡t=t−1=0. Otherwise let a=min⁡{1,t} and b=max⁡{1,t}. By [F2] and [F3], ln⁡ is continuous on [a,b]; by [F5], it is differentiable on (a,b) with derivative 1/u. Applying [F6] gives c∈(a,b) with ln⁡t−ln⁡1=(t−1)/c, so ln⁡t=(t−1)/c by [F4]. If t>1, then c>1; if 0<t<1, then 0<c<1 and t−1<0. In either case (t−1)/c<t−1. Thus ln⁡t≤t−1, with equality only at t=1.

2.1F1A1step 1.1givenalgebra∎

Let S={i:pi>0}. By [F1], [A1], and step 1.1 applied to qi/pi for each i∈S, D(p∥q)=−∑i∈Spiln⁡(qi/pi)≥∑i∈S(pi−qi)=1−∑i∈Sqi≥0. If D(p∥q)=0, both inequalities are equalities. Equality in the last requires qi=0 outside S, and [A1] then forces S=[m]. Equality in the first requires each nonnegative gap from step 1.1, multiplied by pi>0, to vanish; hence qi/pi=1 for every i. Conversely p=q gives D(p∥q)=0 by [F1].

Depends on

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