A measure dominates a family of measures when every member is absolutely continuous with respect to . Any two finite positive measures and have the common dominating measure .
Let be continuous, strictly increasing, and satisfy Lusin condition N. Thendefines a measure on the Lebesgue measurable sets, and . Moreover,for .
If , then exactly when for every there is such that implies . For necessity, a contrary sequence with and has tail unions decreasing to a -null limsup; continuity from above for finite contradicts absolute continuity.
Two probability measures are equivalent when each is absolutely continuous with respect to the other, or equivalently when they have the same null events.
For finite positive measures , put . The linear functional is bounded on real by the Cauchy-Schwarz inequality. The Riesz representation theorem gives a measurable with . Testing indicators of its negative and greater-than-one level sets shows almost everywhere. Subtraction gives . This constructs the densities without assuming the Radon-Nikodym theorem as a prior result.
When , the Radon-Nikodym derivative is the almost-everywhere unique measurable function satisfying .
Mutual absolute continuity is equivalent to the Radon--Nikodym derivative being finite and strictly positive almost everywhere.
Use the Hilbert-space construction of dominated measure densities with . The set is a null set for . Put on and elsewhere. Then and . This is the Lebesgue decomposition into a density part and a part concentrated on a -null set.
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