Simple Function and Its Integral

definitionAnalysisProbability

Simple Function and Its Integral

definitionAnalysisProbabilitydef:simple-function-integral-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}. For AXA\subseteq X, the \textbf{indicator function} 1A:XR\mathbf{1}_A:X\to\mathbb{R} is defined by 1A(x)=1\mathbf{1}_A(x)=1 for xAx\in A and 1A(x)=0\mathbf{1}_A(x)=0 otherwise.

A \textbf{simple function} on (X,F)(X,\mathcal{F}) is a \reftext{def:measurable-function-2026a}{measurable} function s:XRs:X\to\mathbb{R} that takes only finitely many values. Writing c1,,crc_1,\dots,c_r for the distinct values of ss and Ai=s1({ci})A_i=s^{-1}(\{c_i\}), the sets A1,,ArA_1,\dots,A_r are measurable (each {ci}\{c_i\} is a \reftext{def:borel-sigma-algebra-real-line-2026a}{Borel set}), pairwise disjoint, cover XX, and

s=i=1rci1Ai;s=\sum_{i=1}^{r}c_i\,\mathbf{1}_{A_i};

this is the \textbf{standard representation} of ss.

If ss is a nonnegative simple function with standard representation as above, its \textbf{integral} with respect to μ\mu is

Xsdμ=i=1rciμ(Ai)[0,],\int_X s\,d\mu=\sum_{i=1}^{r}c_i\,\mu(A_i)\in[0,\infty],

with the conventions of \ref{def:measure-measure-space-2026a}, in particular 0=00\cdot\infty=0.

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