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On convergence of the distributions of random sequences with independent random indexes to variance–mean mixtures
| Content Provider | Scilit |
|---|---|
| Author | Korolev, Victor Zeifman, A. I. |
| Copyright Year | 2016 |
| Description | We prove a transfer theorem for random sequences with independent random indexes in the double array limit setting under relaxed conditions. We also prove its partial inverse providing the necessary and sufficient conditions for the convergence of randomly indexed random sequences. Special attention is paid to the case where the elements of the basic double array are formed as cumulative sums of independent not necessarily identically distributed random variables. Using simple moment-type conditions we prove the theorem on convergence of the distributions of such sums to normal variance–mean mixtures. |
| Related Links | http://arxiv.org/pdf/1410.1022 |
| Ending Page | 432 |
| Page Count | 19 |
| Starting Page | 414 |
| ISSN | 15326349 |
| e-ISSN | 15324214 |
| DOI | 10.1080/15326349.2016.1155464 |
| Journal | Stochastic Models |
| Issue Number | 3 |
| Volume Number | 32 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2016-03-31 |
| Access Restriction | Open |
| Subject Keyword | Journal: Stochastic Models Applied Mathematics Normal Variance–mean Mixture Random Index Random Lindeberg Condition Random Sequence Random Sum Transfer Theorem 60e07 60f99 |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Statistics and Probability Modeling and Simulation |
