Cramér–Wold theorem

E933486

The Cramér–Wold theorem is a fundamental result in probability theory stating that a multivariate distribution is uniquely determined by the distributions of all its one-dimensional linear projections.

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Cramér–Wold theorem canonical 1

Statements (30)

Predicate Object
instanceOf result in multivariate statistics
theorem in probability theory
appliesTo multivariate probability distributions
random vectors in R^n
category theorems in probability theory
theorems in statistics
conclusion two random vectors with identical distributions of all linear projections have the same multivariate distribution
condition all one-dimensional linear projections must be considered
equality in distribution of all linear projections implies equality in distribution of random vectors
describes characterization of multivariate distributions by one-dimensional projections
domain Euclidean space R^n NERFINISHED
field probability theory
statistics
implies uniqueness of a multivariate distribution from all one-dimensional linear projections
involves linear combinations of components of a random vector
one-dimensional marginal distributions of linear projections
mathematicalForm If a^T X and a^T Y have the same distribution for all a in R^n, then X and Y have the same distribution
namedAfter Harald Cramér NERFINISHED
Herman Wold NERFINISHED
relatedTo Skorokhod representation theorem NERFINISHED
central limit theorem NERFINISHED
characteristic functions in probability theory
weak convergence of probability measures
statement A probability distribution on R^n is uniquely determined by the distributions of all its one-dimensional linear projections
usedFor characterizing weak convergence in R^n
proving convergence in distribution of random vectors
reducing multivariate distribution problems to univariate ones
usedIn asymptotic theory in statistics
multivariate central limit theorem proofs
theory of random vectors

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Harald Cramér knownFor Cramér–Wold theorem