s-finite measures can be written as withDensity of a finite measure #
If μ is an s-finite measure, then there exists a finite measure μ.toFinite
such that a set is μ-null iff it is μ.toFinite-null.
In particular, MeasureTheory.ae μ.toFinite = MeasureTheory.ae μ and μ.toFinite = 0 iff μ = 0.
As a corollary, μ can be represented as μ.toFinite.withDensity (μ.rnDeriv μ.toFinite).
Our definition of MeasureTheory.Measure.toFinite ensures some extra properties:
- if
μis a finite measure, thenμ.toFinite = μ[|univ] = (μ univ)⁻¹ • μ; - in particular,
μ.toFinite = μfor a probability measure; - if
μ ≠ 0, thenμ.toFiniteis a probability measure.
Main definitions #
In this definition and the results below, μ is an s-finite measure (SFinite μ).
MeasureTheory.Measure.toFinite: a finite measure withμ ≪ μ.toFiniteandμ.toFinite ≪ μ. Ifμ ≠ 0, this is a probability measure.
Main statements #
absolutelyContinuous_toFinite:μ ≪ μ.toFinite.toFinite_absolutelyContinuous:μ.toFinite ≪ μ.ae_toFinite:ae μ.toFinite = ae μ.
Auxiliary definition for MeasureTheory.Measure.toFinite.
Equations
Instances For
A finite measure obtained from an s-finite measure μ, such that
μ = μ.toFinite.withDensity (μ.rnDeriv µ.toFinite)
(see MeasureTheory.Measure.withDensity_rnDeriv_eq along with
MeasureTheory.absolutelyContinuous_toFinite). If μ is non-zero, then μ.toFinite is a
probability measure.