# Jensen's inequality

(Difference between revisions)
 Revision as of 12:59, 26 July 2008 (edit)← Previous diff Revision as of 13:02, 26 July 2008 (edit) (undo)Next diff → Line 22: Line 22: and $\,f\,$ is constant on each $\,X_j\,$ . and $\,f\,$ is constant on each $\,X_j\,$ . - Say $\,t_j=\mu(X_j)\,$ and $\,a_j\,$ is the value of $\,f\,$ on $\,X_j\,$. + Say $\,t_j=\mu(X_j)\,$ and $\,a_j\,$ is the value of $\,f\,$ on $\,X_j\,$ .  + Then (1) and (2) say exactly the same thing. QED. Then (1) and (2) say exactly the same thing. QED. Line 38: Line 39: Let $\,m\,$ be the right derivative of $\,\phi\,$ Let $\,m\,$ be the right derivative of $\,\phi\,$ - at $\,a\,$, and let + at $\,a\,$ ,  and let $\,L(t) = \phi(a) + m(t-a)\,$ $\,L(t) = \phi(a) + m(t-a)\,$ The bullets above say $\,\phi(t)\geq L(t)\,$ for The bullets above say $\,\phi(t)\geq L(t)\,$ for - all $\,t\,$ in the domain of $\,\phi\,$ .  So + all $\,t\,$ in the domain of  $\,\phi\,$ .  So [itex]\begin{array}{rl}\int \phi \circ f &\geq \int L \circ f\\ [itex]\begin{array}{rl}\int \phi \circ f &\geq \int L \circ f\\

## Revision as of 13:02, 26 July 2008

By definition $LaTeX: \,\phi\,$ is convex if and only if $LaTeX: \phi(ta + (1-t)b) \leq t \phi(a) + (1-t) \phi(b)$

whenever $LaTeX: \,0 \leq t \leq 1\,$ and $LaTeX: \,a\,, b\,$ are in the domain of $LaTeX: \,\phi\,$.

It follows by induction on $LaTeX: \,n\,$ that if $LaTeX: \,t_j \geq 0\,$ for $LaTeX: \,j = 1, 2\ldots n\,$ then $LaTeX: \phi(\sum t_j a_j) \leq \sum t_j \phi(a_j)$           (1)

Jensen's inequality says this:
If $LaTeX: \,\mu\,$ is a probability measure on $LaTeX: \,X\,$, $LaTeX: \,f\,$ is a real-valued function on $LaTeX: \,X\,$, $LaTeX: \,f\,$ is integrable, and $LaTeX: \,\phi\,$ is convex on the range of $LaTeX: \,f\,$ then $LaTeX: \phi(\int f d \mu) \leq \int \phi \circ f d \mu\qquad$          (2)

Proof 1: By some limiting argument we can assume that $LaTeX: \,f\,$ is simple. (This limiting argument is a missing detail to this proof...)
That is, $LaTeX: \,X\,$ is the disjoint union of $LaTeX: \,X_1 \,\ldots\, X_n\,$ and $LaTeX: \,f\,$ is constant on each $LaTeX: \,X_j\,$ .

Say $LaTeX: \,t_j=\mu(X_j)\,$ and $LaTeX: \,a_j\,$ is the value of $LaTeX: \,f\,$ on $LaTeX: \,X_j\,$ .

Then (1) and (2) say exactly the same thing. QED.

Proof 2:

Lemma. If $LaTeX: \,a < b,\, \,a' < b',\, \,a \leq a'\,$ and $LaTeX: \,b \leq b'\,$ then $LaTeX: \,(f(a) - f(b)) / (a - b) \leq (f(a') - f(b')) / (a' - b')\quad\diamond$

The lemma shows:

• $LaTeX: \,\phi\,$ has a right-hand derivative at every point, and
• the graph of $LaTeX: \,\phi\,$ lies above the "tangent" line through any point on the graph with slope equal to the right derivative.

Say $LaTeX: \,a = \int f d \mu\,$

Let $LaTeX: \,m\,$ be the right derivative of $LaTeX: \,\phi\,$ at $LaTeX: \,a\,$ ,  and let $LaTeX: \,L(t) = \phi(a) + m(t-a)\,$

The bullets above say $LaTeX: \,\phi(t)\geq L(t)\,$ for all $LaTeX: \,t\,$ in the domain of $LaTeX: \,\phi\,$ .  So $LaTeX: \begin{array}{rl}\int \phi \circ f &\geq \int L \circ f\\

 &= \int (\phi(a) + m(f - a))\\ &= \phi(a) + (m \int f) - ma\\ &= \phi(a)\\ &= \phi(\int f)\end{array}$ $LaTeX: \,-\,$D. Ullrich