TheoremBase

If the mean had no value of f below it, f minus the mean would be a nonnegative function with integral zero, hence would vanish somewhere, so the mean is a value of f; together with the interval property this puts the mean in I. Integrating the supporting line of the convex function at the mean then gives Jensen's inequality.

Proof

Write m=∫Xf dμm=\int_{X}f\,d\mu. Throughout, constants are integrated through 1X\mathbf{1}_{X}, the map X→RX\to\mathbb{R} with value 11 everywhere (Indicator Function of a Subset (i)): it is measurable by Measurable Maps: Generators, Composition, Continuous Maps, Restrictions, and Criteria for Real- and [0,∞]-Valued Maps (iii), it lies in M+\mathcal{M}^{+} with ∫X1X dμ=μ(X)=1\int_{X}\mathbf{1}_{X}\,d\mu=\mu(X)=1 by Basic Properties of the Integral of Nonnegative Measurable Maps (ii) and Measure, Measure Space, and Probability Measure (v), and so it lies in L1(μ)\mathcal{L}^{1}(\mu) with integral 11 by Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion (vi). Hence, by Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion (vii), for all h∈L1(μ)h\in\mathcal{L}^{1}(\mu) and a,b∈Ra,b\in\mathbb{R} the function ah+b1Xah+b\mathbf{1}_{X}, x↦ah(x)+bx\mapsto ah(x)+b, lies in L1(μ)\mathcal{L}^{1}(\mu) and

∫X(ah+b1X) dμ=a∫Xh dμ+b.\int_{X}\bigl(ah+b\mathbf{1}_{X}\bigr)\,d\mu=a\int_{X}h\,d\mu+b .

Step 1: the mean lies in II. Suppose first that no p∈Ip\in I satisfies p<mp<m. Since f(x)∈If(x)\in I, then f(x)≥mf(x)\ge m for every x∈Xx\in X. By the opening display the function g=f−m1Xg=f-m\mathbf{1}_{X} lies in L1(μ)\mathcal{L}^{1}(\mu) with ∫Xg dμ=m−m=0\int_{X}g\,d\mu=m-m=0; it is measurable with nonnegative values, so by Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion (vi) it lies in M+\mathcal{M}^{+} and its integral as an element of M+\mathcal{M}^{+} is 00. By The Lebesgue Integral and Null Sets (iv), μ({x∈X:g(x)>0})=0\mu(\{x\in X:g(x)>0\})=0. Since μ(X)=1\mu(X)=1, this set is not XX, so there is x0∈Xx_{0}\in X with g(x0)=0g(x_{0})=0, that is, m=f(x0)∈Im=f(x_{0})\in I. In the same way, applied to m1X−fm\mathbf{1}_{X}-f, if no q∈Iq\in I satisfies q>mq>m then m∈Im\in I. In the remaining case there are p,q∈Ip,q\in I with p<m<qp<m<q, and m∈Im\in I by Intervals of the Real Line (i). This proves (i).

Step 2: integrating a supporting line. Since m∈Im\in I, Convex Functions on an Open Interval: Monotone Slopes, Supporting Lines, Continuity, and the Supremum of Rational Supporting Lines (ii) provides the real number c=cmc=c_{m}, and Convex Functions on an Open Interval: Monotone Slopes, Supporting Lines, Continuity, and the Supremum of Rational Supporting Lines (iii), applied at mm and f(x)∈If(x)\in I, gives

φ(f(x))≥φ(m)+c (f(x)−m)=c f(x)+(φ(m)−c m)(x∈X).\varphi\bigl(f(x)\bigr)\ge\varphi(m)+c\,\bigl(f(x)-m\bigr)=c\,f(x)+\bigl(\varphi(m)-c\,m\bigr)\qquad(x\in X).

By the opening display the right-hand side, as a function of xx, is cf+(φ(m)−cm)1X∈L1(μ)cf+(\varphi(m)-cm)\mathbf{1}_{X}\in\mathcal{L}^{1}(\mu), with integral c m+φ(m)−c m=φ(m)c\,m+\varphi(m)-c\,m=\varphi(m). Since φ∘f∈L1(μ)\varphi\circ f\in\mathcal{L}^{1}(\mu), Linearity and Monotonicity of the Lebesgue Integral, and the Integrability Criterion (ix) gives

φ(m)=∫X(cf+(φ(m)−cm)1X) dμ≤∫Xφ∘f dμ,\varphi(m)=\int_{X}\bigl(cf+(\varphi(m)-cm)\mathbf{1}_{X}\bigr)\,d\mu\le\int_{X}\varphi\circ f\,d\mu,

which is (ii).

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