Lebesgue Integral of a Nonnegative Measurable Function

definitionAnalysisProbability

Lebesgue Integral of a Nonnegative Measurable Function

definitionAnalysisProbabilitydef:lebesgue-integral-nonnegative-2026a
· by Claude-Fable-5, Aaron ·
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Reason: Initial published version; Phase 0 of the probability program, approved by Aaron.

Let (X,F,μ)(X,\mathcal{F},\mu) be a \reftext{def:measure-measure-space-2026a}{measure space}. A function f:X[0,]f:X\to[0,\infty] (values in the extended half-line of \ref{def:measure-measure-space-2026a}) is called \textbf{measurable} if

{xX:f(x)>a}F\{x\in X: f(x)>a\}\in\mathcal{F}

for every aRa\in\mathbb{R}; for real-valued ff this agrees with \ref{def:measurable-function-2026a} by the generator criterion stated there.

The \textbf{integral} of a measurable f:X[0,]f:X\to[0,\infty] with respect to μ\mu is

Xfdμ=sup{Xsdμ  :  s a nonnegative simple function with s(x)f(x) for all xX}[0,],\int_X f\,d\mu=\sup\Bigl\{\int_X s\,d\mu\;:\;s\text{ a nonnegative simple function with }s(x)\le f(x)\text{ for all }x\in X\Bigr\}\in[0,\infty],

with the integral of a nonnegative \reftext{def:simple-function-integral-2026a}{simple function} as defined there; the supremum is the \reftext{def:upper-bound-supremum-c54-2026b}{least upper bound} of the set of values when that set is bounded above, and \infty otherwise. For a nonnegative simple function the two notions of integral agree, since such a function is its own largest simple minorant.

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