Zobrazeno 1 - 10
of 52
pro vyhledávání: '"de la Peña, Victor H."'
We obtain concentration and large deviation for the sums of independent and identically distributed random variables with heavy-tailed distributions. Our concentration results are concerned with random variables whose distributions satisfy $\mathbb{P
Externí odkaz:
http://arxiv.org/abs/2003.13819
Publikováno v:
Probability Surveys 2007, Vol. 4, 172-192
Self-normalized processes are basic to many probabilistic and statistical studies. They arise naturally in the the study of stochastic integrals, martingale inequalities and limit theorems, likelihood-based methods in hypothesis testing and parameter
Externí odkaz:
http://arxiv.org/abs/0709.2233
Publikováno v:
IMS Lecture Notes--Monograph Series 2006, Vol. 49, 183-209
In this paper, we obtain general representations for the joint distributions and copulas of arbitrary dependent random variables absolutely continuous with respect to the product of given one-dimensional marginal distributions. The characterizations
Externí odkaz:
http://arxiv.org/abs/math/0611166
Publikováno v:
Annals of Probability 2004, Vol. 32, No. 3A, 1902-1933
Self-normalized processes arise naturally in statistical applications. Being unit free, they are not affected by scale changes. Moreover, self-normalization often eliminates or weakens moment assumptions. In this paper we present several exponential
Externí odkaz:
http://arxiv.org/abs/math/0410102
Publikováno v:
Proceedings of the American Mathematical Society, 2004 Aug 01. 132(8), 2465-2474.
Externí odkaz:
https://www.jstor.org/stable/4097477
Publikováno v:
Journal of Applied Probability, 2004 Jan 01. 41, 145-156.
Externí odkaz:
https://www.jstor.org/stable/3215974
Publikováno v:
The Annals of Probability, 2003 Apr 01. 31(2), 630-675.
Externí odkaz:
https://www.jstor.org/stable/3481656
Autor:
de la Pena, Victor H.
Publikováno v:
The Annals of Probability, 1999 Jan 01. 27(1), 537-564.
Externí odkaz:
https://www.jstor.org/stable/2652884
Publikováno v:
Annals Prob. 23, (1995), 806-816
In this paper the following result, which allows one to decouple U-Statistics in tail probability, is proved in full generality. Theorem 1. Let $X_i$ be a sequence of independent random variables taking values in a measure space $S$, and let $f_{i_1.
Externí odkaz:
http://arxiv.org/abs/math/9309211
Publikováno v:
Bull. Amer. Math. Soc. (N.S.) 31 (1994) 223-227
The authors announce a general tail estimate, called a decoupling inequality, for a symmetrized sum of non-linear $k$-correlations of $n>k$ independent random variables.
Comment: 5 pages. Abstract added in migration.
Comment: 5 pages. Abstract added in migration.
Externí odkaz:
http://arxiv.org/abs/math/9309210