2009Applicable AnalysisRequires access

Uniform measures on inverse limit spaces

David R. Stockman

Open publisher page 3 citations

Abstract

Motivated by problems from dynamic economic models, we consider the problem of defining a uniform measure on inverse limit spaces. Let where X is a compact metric space and f is continuous, onto and piecewise one-to-one and . Then starting with a measure μ1 on the Borel sets , we recursively construct a sequence of probability measures on satisfying for each and . This sequence of probability measures is then uniquely extended to a probability measure on the inverse limit space Y. If μ1 is a uniform measure, we argue that the measure induced on the inverse limit space by the recursively constructed sequence of measures is a uniform measure. As such, the measure has uses in economic theory for policy evaluation and in dynamical systems in providing an ambient measure (when Lebesgue measure is not available) with which to define a Sinai–Ruelle–Bowen (SRB) measure or a metric attractor for the shift map on the inverse limit space.

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Motivated by problems from dynamic economic models, we consider the problem of defining a uniform measure on inverse limit spaces. Let where X is a compact metric space and f is continuous, onto and piecewise one-to-one and . Then starting with a measure μ1 on the Borel sets , we recursively construct a sequence of probability measures on satisfying for each and . This sequence of probability measures is then uniquely extended to a probability measure on the inverse limit space Y. If μ1 is a uniform measure, we argue that the measure induced on the inverse limit space by the recursively constructed sequence of measures is a uniform measure. As such, the measure has uses in economic theory for policy evaluation and in dynamical systems in providing an ambient measure (when Lebesgue measure is not available) with which to define a Sinai–Ruelle–Bowen (SRB) measure or a metric attractor for the shift map on the inverse limit space.

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Available abstract

Motivated by problems from dynamic economic models, we consider the problem of defining a uniform measure on inverse limit spaces. Let where X is a compact metric space and f is continuous, onto and piecewise one-to-one and . Then starting with a measure μ1 on the Borel sets , we recursively construct a sequence of probability measures on satisfying for each and . This sequence of probability measures is then uniquely extended to a probability measure on the inverse limit space Y. If μ1 is a uniform measure, we argue that the measure induced on the inverse limit space by the recursively constructed sequence of measures is a uniform measure. As such, the measure has uses in economic theory for policy evaluation and in dynamical systems in providing an ambient measure (when Lebesgue measure is not available) with which to define a Sinai–Ruelle–Bowen (SRB) measure or a metric attractor for the shift map on the inverse limit space.

Key concepts: Mathematics, Measure (data warehouse), Probability measure, Lebesgue measure, σ-finite measure, Inverse limit, Borel measure, Limit (mathematics)

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