
\((X, \mathcal{M}, \mu)\) is a finite measure space with associated outer measure \( \mu^{*}\): for any \(A \subset X, \mu^{*}(A) = \inf \{ \mu(B): B \in \mathcal{M}, B \supset A \}\), and \((Y, d_{Y})\) is a metric space. A function \( f: X \to Y\) is said to be \(\mathcal{M}\)-measurable if \( f^{-1} (U) \in \mathcal{M}\) for every open set \(U\) in \(Y\). For a sequence \( \{ f_{n}: X \to Y \}\) and an \( f: X \to Y\) (these functions are not necessarily measurable), \( f_{n}\) is defined to be convergent to \(f\) in outer measure if for any \( \varepsilon >0\), \( \mu^{*} (\{x: d_{Y}( f_{n}(x), f(x)) \geq \varepsilon\}) \to 0 \). Using this definition, the author extends the known results about preservation of convergence in measure, by taking composition, to the following main result of the paper: \( (X, \mathcal{M}, \mu)\) is a finite measure space, \((Y, d_{Y}), \; (Z, d_{Z}) \) are metric spaces, \( \{ f_{n}: X \to Y \}\) is a sequence of functions, \( \{ f: X \to Y \}\) an \(\mathcal{M}\)-measurable function, and \( \{ g: Y \to Z \}\) such that \(g\) is continuous on \(f(X)\). If \( f_{n}\) is convergent to \(f\) in outer measure, then \(g \circ f_{n}\) converges to \(g \circ f\) in outer measure.
Convergence in measure, Outer measure, Applied Mathematics, Spaces of measures, convergence of measures, outer measure, convergence in probability, Convergence in probability, Contents, measures, outer measures, capacities, Analysis
Convergence in measure, Outer measure, Applied Mathematics, Spaces of measures, convergence of measures, outer measure, convergence in probability, Convergence in probability, Contents, measures, outer measures, capacities, Analysis
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