Cramér–Wold theorem

In mathematics, the Cramér–Wold theorem in measure theory states that a Borel probability measure on $\mathbb {R} ^{k}$ is uniquely determined by the totality of its one-dimensional projections. It is used as a method for proving joint convergence results. The theorem is named after Harald Cramér and Herman Ole Andreas Wold.

Let

${\overline {X}}_{n}=(X_{n1},\dots ,X_{nk})$

and

$\;{\overline {X}}=(X_{1},\dots ,X_{k})$

be random vectors of dimension k. Then ${\overline {X}}_{n}$ converges in distribution to ${\overline {X}}$ if and only if:

$\sum _{i=1}^{k}t_{i}X_{ni}{\overset {D}{\underset {n\rightarrow \infty }{\rightarrow }}}\sum _{i=1}^{k}t_{i}X_{i}.$

for each $(t_{1},\dots ,t_{k})\in \mathbb {R} ^{k}$, that is, if every fixed linear combination of the coordinates of ${\overline {X}}_{n}$ converges in distribution to the correspondent linear combination of coordinates of ${\overline {X}}$.

References

• This article incorporates material from Cramér-Wold theorem on PlanetMath, which is licensed under the Creative Commons Attribution/Share-Alike License.
• Billingsley, Patrick (1995). Probability and Measure (3 ed.). John Wiley & Sons. ISBN 978-0-471-00710-4. {{cite book}}: Invalid |ref=harv (help)
• Cramér, Harald; Wold, Herman (1936). "Some Theorems on Distribution Functions". Journal of the London Mathematical Society. 11 (4): 290–294. doi:10.1112/jlms/s1-11.4.290.

External links

• Project Euclid: "When is a probability measure determined by infinitely many projections?"