Prakasa Rao, B. L. S. (2009) Conditional independence, conditional mixing and conditional association Annals of the Institute of Statistical Mathematics, 61 (2). pp. 441-460. ISSN 0020-3157
Full text not available from this repository.
Official URL: http://www.springerlink.com/content/4g0037744326j5...
Related URL: http://dx.doi.org/10.1007/s10463-007-0152-2
Abstract
Some properties of conditionally independent random variables are studied. Conditional versions of generalized Borel-Cantelli lemma, generalized Kolmogorov's inequality and generalized Hájek-Rényi inequality are proved. As applications, a conditional version of the strong law of large numbers for conditionally independent random variables and a conditional version of the Kolmogorov's strong law of large numbers for conditionally independent random variables with identical conditional distributions are obtained. The notions of conditional strong mixing and conditional association for a sequence of random variables are introduced. Some covariance inequalities and a central limit theorem for such sequences are mentioned.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Springer. |
| Keywords: | Conditional Independence; Conditional Mixing; Conditional Association; Conditional Borel-Cantelli Lemma; Generalized Kolmogorov Inequality; Conditional Hájek-Rényi Inequality; Conditional Strong Law of Large Numbers; Conditional Central Limit Theorem; Conditional Covariance Inequality |
| ID Code: | 37755 |
| Deposited On: | 26 Apr 2011 12:49 |
| Last Modified: | 26 Apr 2011 12:50 |
Repository Staff Only: item control page
