Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-25T17:42:27.928Z Has data issue: false hasContentIssue false
  • English
  • Français

Central Limit Theorems for Interchangeable Processes

Published online by Cambridge University Press:  20 November 2018

J. R. Blum ,
H. Chernoff ,
M. Rosenblatt  and
H. Teicher
J. R. Blum
Affiliation:
Indiana University
H. Chernoff
Affiliation:
Stanford University
M. Rosenblatt
Affiliation:
Purdue University
H. Teicher
Affiliation:
Purdue University
Rights & Permissions [Opens in a new window]

Extract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Let {Xn} (n = 1, 2 , …) be a stochastic process. The random variables comprising it or the process itself will be said to be interchangeable if, for any choice of distinct positive integers i1, i2, H3 … , ik, the joint distribution of

depends merely on k and is independent of the integers i1, i2, … , ik. It was shown by De Finetti (3) that the probability measure for any interchangeable process is a mixture of probability measures of processes each consisting of independent and identically distributed random variables.

Type
Research Article
Information
Canadian Journal of Mathematics , Volume 10 , 1958 , pp. 222 - 229
Copyright
Copyright © Canadian Mathematical Society 1958

References

1. Berry, A. C., The accuracy of the Gaussian approximation to the sum of independent variâtes, Trans. Amer. Math. Soc, 49 (1941), 122-136.Google Scholar
2. Cramer, Harold, Random variables and probability distributions, Cambridge Tracts in Mathematics, 136 (Cambridge, 1937).Google Scholar
3. Finetti, Bruno De, La prévision, ses lois logiques, ses sources subjectives, Annales de l'Institut Henri Poincaré, 7 (1937), 1-68.Google Scholar
4. Esseen, Carl-Gustav, Fourier analysis of distribution functions, Acta Math., 77 (1944), 1–125.Google Scholar