A subset of X is measurable relative to a sigma-algebra F when it belongs to F. A measure defined on F assigns sizes to these sets. Measurability depends on the chosen sigma-algebra; for example, a Lebesgue measurable set need not be a Borel set.
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- Absolute continuity of the Lebesgue integral
- Complete measure
- Conditional distribution
- Countability of point atoms of a finite measure
- Countable additivity
- Counting measure
- Density of continuous functions in Lp on an interval
- Dirac measure
- Disjoint observation windows
- Event
- Finite-measure set
- Finite-prefix invariance of tail events
- Finite supremum of positive measures
- Hahn decomposition
- Homogeneous Poisson point process
- Independent and identically distributed random variables
- Independent random variables
- Inner regular measure
- Laplace functional of a Poisson random measure
- Lebesgue integral
- Lebesgue integration
- Lévy measure
- Markov process
- Maximal additivity algebra of a regular outer measure
- Measurable-factor rule for conditional expectation
- Measurable probability kernel
- Measure
- Measure theory
- Monotonicity of a measure
- Non-homogeneous Poisson point process
- Null set
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- Phi-irreducibility
- Point atom of a measure
- Poisson point process
- Poisson random measure
- Positive Harris recurrent Markov chain
- Preimage
- Probability distribution
- Regular outer measure
- Restriction of a measure to a measurable subset
- Set function
- Set of finite perimeter
- Signed measure
- Steiner symmetrization
- Step function
- Superposition theorem for Poisson point processes
- Total variation distance
- Trace sigma-algebra
- Truncated normal distribution
- Vector measure
- Void probability functional
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