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Tightness from characteristic function equicontinuity at zero
Statement
Assume AC. Let be a family of Borel probability laws on . For put . Every satisfies If the characteristic functions are equicontinuous at zero, meaning that for every some satisfies for every and , then is tight. AC supplies the countable choice used by the compact-interval integration bridge and the continuous-integrand calculus.
Facts & Assumptions
Given: The hypotheses and conventions in the statement.
The real part of the characteristic function is the integral of cosine. Characteristic function of a real random variable.
Fubini applies to absolutely integrable functions on sigma-finite products. Fubini's theorem for L^1 functions on a sigma-finite product.
An integrable derivative is evaluated by its primitive. The second fundamental theorem: if is differentiable on with and is integrable, then .
Under countable choice the bounded Riemann integral agrees with the Lebesgue integral. A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral.
AC implies the countable choice used by the integration bridge. The Axiom of Choice.
Tightness requires a single compact set for each error and the whole family. Tight family of probability measures.
Sine and cosine have derivatives cosine and minus sine. The derivatives of sine and cosine are cosine and minus sine.
Integration by parts holds for differentiable functions with integrable derivatives. If are differentiable on with integrable, then .
The cosine is real with absolute value at most one. , , and .
Proof
The continuous nonnegative weight is supported on and has integral . Set . At it equals one. For , integration by parts on , with and , gives All functions and their derivatives here are continuous on that interval; the primitive and integration bridge therefore apply. The formula gives , while its defining integral and give . Also when , including equality in the cutoff.
The function is jointly Borel, nonnegative, and has product integral at most : Lebesgue measure is sigma-finite and is finite. Fubini and the characteristic-function definition yield Nonnegativity off the tail justifies discarding its complement. Rearrangement proves the quantitative assertion.
Given , equicontinuity supplies with whenever , uniformly in . Choose . The weight has mass one, so the integral in the bound is at most . Thus for every member. The interval is compact, proving tightness. For an empty family the empty compact set suffices. A singleton family and an atom at zero satisfy the same calculation (the latter has zero right-hand side). There is no assertion at , where the weight is undefined.
Depends on
- Characteristic function of a real random variable
- Fubini's theorem for L^1 functions on a sigma-finite product
- The second fundamental theorem: if $G$ is differentiable on $[a,b]$ with $G' = f$ and $f$ is integrable, then $\int_a^b f = G(b)-G(a)$
- A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral
- The Axiom of Choice
- Tight family of probability measures
- The derivatives of sine and cosine are cosine and minus sine
- If $u,v$ are differentiable on $[a,b]$ with $u',v'$ integrable, then $\int_a^b u v' = u(b)v(b)-u(a)v(a) - \int_a^b u'v$
- Heine-Borel in $\mathbb{R}^n$: with the Euclidean metric a subset of $\mathbb{R}^n$ is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line
- $\exp(x+iy)=e^x(\cos y+i\sin y)$, $|\exp(x+iy)|=e^x$, and $e^{i\pi}+1=0$
Used by
- Levy continuity theorem converse Theorem
Dependency tree · two levels
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Sources
- Durrett, Probability: Theory and Examples, fifth edition (standard reference, not scraped)
- Norris, Probability and Measure (standard reference, not scraped)