In probability theory, a standard probability space, also called Lebesgue–Rokhlin probability space or just Lebesgue space (the latter term is ambiguous) is a probability space satisfying certain assumptions introduced by Vladimir Rokhlin in 1940. Informally, it is a probability space consisting of an interval and/or a finite or countable number of atoms.
The theory of standard probability spaces was started by von Neumann in 1932 and shaped by Vladimir Rokhlin in 1940. Rokhlin showed that the unit interval endowed with the Lebesgue measure has important advantages over general probability spaces, yet can be effectively substituted for many of these in probability theory. The dimension of the unit interval is not an obstacle, as was clear already to Norbert Wiener. He constructed the Wiener process (also called Brownian motion) in the form of a measurable map from the unit interval to the space of continuous functions.
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In probability theory, a standardprobabilityspace, also called Lebesgue–Rokhlin probabilityspace or just Lebesgue space (the latter term is ambiguous)...
In probability theory, a probabilityspace or a probability triple ( Ω , F , P ) {\displaystyle (\Omega ,{\mathcal {F}},P)} is a mathematical construct...
family of standard Borel spaces are standard. Every complete probability measure on a standard Borel space turns it into a standardprobabilityspace. Theorem...
Lebesgue space may refer to: Lp space, a special Banach space of functions (or rather, equivalence classes of functions) Standardprobabilityspace, a non-pathological...
In probability theory, the sample space (also called sample description space, possibility space, or outcome space) of an experiment or random trial is...
inequality Probability theory Probabilityspace Sample spaceStandardprobabilityspace Random element Random compact set Dynkin system Probability axioms...
In probability theory, the law (or formula) of total probability is a fundamental rule relating marginal probabilities to conditional probabilities. It...
applications Standard deviation Standard error Standard normal deviate Standard normal table StandardprobabilityspaceStandard score Standardized coefficient...
not of a theoretical sample space but of an actual experiment. More generally, empirical probability estimates probabilities from experience and observation...
Borel. See analytic set. Every probability measure on a standard Borel space turns it into a standardprobabilityspace. An example of a subset of the...
random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the...
The standardprobability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. These axioms remain...
In probability and statistics, a probability mass function (sometimes called probability function or frequency function) is a function that gives the...
measure theory) Sample spaces, σ-algebras and probability measures Probabilityspace Sample spaceStandardprobabilityspace Random element Random compact...
because the countable direct product of a standardprobabilityspace is again a standardprobabilityspace. As a further generalization, one may replace...
axioms formalise probability in terms of a probabilityspace, which assigns a measure taking values between 0 and 1, termed the probability measure, to a...
In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose...
probabilities means representing probabilities on a logarithmic scale ( − inf , 0 ] {\displaystyle (-\inf ,0]} , instead of the standard [ 0 , 1 ] {\displaystyle...
function as the probability amplitude is a pillar of the Copenhagen interpretation of quantum mechanics. In fact, the properties of the space of wave functions...
Rokhlin partitions. He introduced the notion of standardprobabilityspace, and characterised such spaces up to isomorphism mod 0. He also proved the famous...
In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued...
In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes...
A prior probability distribution of an uncertain quantity, often simply called the prior, is its assumed probability distribution before some evidence...
variables that are defined on the same probabilityspace, the joint probability distribution is the corresponding probability distribution on all possible pairs...
In probability theory, there exist several different notions of convergence of sequences of random variables, including convergence in probability, convergence...
Probability theory and statistics have some commonly used conventions, in addition to standard mathematical notation and mathematical symbols. Random variables...