in this paper, strong laws of large numbers (slln) are obtained for the sums ƒ°=nii x1, undercertain conditions, where {x ,n . 1} n is a sequence of pairwise negatively dependent random variables.

a random walk on a lattice is one of the most fundamental models in probability theory. when the random walk is inhomogenous and its inhomogeniety comes from an ergodic stationary process, the walk is called a random walk in a random environment (rwre). the basic questions such as the law of large numbers (lln), the central limit theorem (clt), and the large deviation principle (ldp) are no...

Petrov (1996) proved the connection between general moment conditions and the applicability of the strong law of large numbers to a sequence of pairwise independent and identically distributed random variables. This note examines this connection to a sequence of pairwise negative quadrant dependent (NQD) and identically distributed random variables. As a consequence of the main theorem ...

in this paper, we extend some famous maximal inequalities and obtain strong laws of largenumbers for arbitrary random variables by use of these inequalities and martingale techniques.

In this paper, the concepts of positive dependence and linearlypositive quadrant dependence are introduced for fuzzy random variables. Also,an inequality is obtained for partial sums of linearly positive quadrant depen-dent fuzzy random variables. Moreover, a weak law of large numbers is estab-lished for linearly positive quadrant dependent fuzzy random variables. Weextend some well known inequ...

Benford’s law predicts the frequency of the first digit of numbers met in a wide range of naturally occurring phenomena. In data sets, following Benford’s law, numbers are started with a small leading digit more often than those with a large leading digit. This law can be used as a tool for detecting fraud and abnormally in the number sets and any fabricated number sets. This can be used as an ...