Probability theory

Klenke, A. (2008). Probability theory: a comprehensive course. Springer.

Type

Book chapter

Intellectual base

Review or monograph

Year

2008

DOI

10.1007/978-1-84800-048-3_24

Link

https://doi.org/10.1007/978-1-84800-048-3_24

Cited by

5 citations across 5 artifacts.

Domain-specific

• Σ-Algebra of τ-past
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.
• Gamma process
  • … demonstrates that the time parameter, shape activity and rate or scale convention, independent stationary increment law, initial value, path regularity, and any drift convention are explicit. to An applied instance preserves the same invariant under a changed scale, notation, jurisdiction, dataset, or implementation..
• Measurable space
  • The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.
• Random measure
  • A random measure makes the entire allocation of mass random rather than only a scalar observation.
• Sub-probability measure
  • A sub-probability measure relaxes only the unit-total-mass axiom of a probability measure.

Verification

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Registry ID ref:19c4c450422f · see in the full table