Keywords: Fuzzy variable Independence Operation t-norm Convergence Law of large numbers a b s t r a c t T-independence of fuzzy variables is a more general concept than the classical independence. The objective of this study is to deal with some new properties of T-independent fuzzy variables. First of all, for any general t-norm, some criteria of T-independence are discussed for fuzzy variable...

Ordinal categorial variables are a common case in regression modeling. Although the case of ordinal response variables has been well investigated, less work has been done concerning ordinal predictors. This article deals with the selection of ordinally scaled independent variables in the classical linear model, where the ordinal structure is taken into account by use of a difference penalty on ...

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The paper deals with a problem proposed by Uriel Feige in 2005: if X1, . . . , Xn is a set of independent nonnegative random variables with expectations equal to 1, is it true that P ( ∑n i=1 Xi < n + 1) > 1 e ? He proved that P ( ∑n i=1Xi < n + 1) > 1 13 . In this paper we prove that infimum of the P ( ∑n i=1Xi < n + 1) can be achieved when all random variables have only two possible values, a...

We will examine double sequence to double sequence transformation of independent identically distribution random variables with respect to four-dimensional summability matrix methods. The main goal of this paper is the presentation of the following theorem. If maxk,l|am,n,k,l| maxk,l|am,kan,l| O m−γ1 O n−γ2 , γ1, γ2 > 0, then E|X̆|1 1/γ1 < ∞ and E| ̆̆ X|1 1/γ2 < ∞ imply that Ym,n → μ almost sure P...

We obtain an improvement of strong laws of large numbers for independent fuzzy random variables.

♣ Let X and Y be two discrete r.v.'s and let R be the corresponding space of X and Y. The joint p.d.f. of X = x and Y = y, denoted by f (x, y) = P (X = x, Y = y), has the following properties: (a) 0 ≤ f (x, y) ≤ 1, f (x, y) ≥ 0 for − ∞ < x, y < ∞. ∞ −∞ ∞ −∞ f (x, y)dxdy = 1. y f (x, y) (∞ −∞ f (x, y)dy), x ∈ R x. ♣ The marginal p.d.f. of Y is defined as f Y (y) = x f (x, y) (∞ −∞ f (x, y)dx), y...