The Strong Law of Large Numbers for Extended Negatively Dependent Random Variables
نویسندگان
چکیده
منابع مشابه
MARCINKIEWICZ-TYPE STRONG LAW OF LARGE NUMBERS FOR DOUBLE ARRAYS OF NEGATIVELY DEPENDENT RANDOM VARIABLES
In the following work we present a proof for the strong law of large numbers for pairwise negatively dependent random variables which relaxes the usual assumption of pairwise independence. Let be a double sequence of pairwise negatively dependent random variables. If for all non-negative real numbers t and , for 1 < p < 2, then we prove that (1). In addition, it also converges to 0 in ....
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in the following work we present a proof for the strong law of large numbers for pairwise negatively dependent random variables which relaxes the usual assumption of pairwise independence. let be a double sequence of pairwise negatively dependent random variables. if for all non-negative real numbers t and , for 1 < p < 2, then we prove that (1). in addition, it also converges to 0 in . the res...
متن کاملThe Strong Law of Large Numbers for Extended Negatively Dependent Random Variables
A sequence of random variables is said to be extended negatively dependent (END) if the tails of its finite-dimensional distributions in the lower-left and upper-right corners are dominated by a multiple of the tails of the corresponding finite-dimensional distributions of a sequence of independent random variables with the samemarginal distributions. The goal of this paper is to establish the ...
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ژورنال
عنوان ژورنال: Journal of Applied Probability
سال: 2010
ISSN: 0021-9002,1475-6072
DOI: 10.1239/jap/1294170508